DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on September 8, 2026 has been entered.
Status of Claims
Claims 1-6, 8, and 11, as recited in an amendment filed on February 10, 2026, were previously pending and subject to a final office action filed on April 6, 2026 (the “April 6, 2026 Final Office Action”). On September 8, 2026, Applicant filed a Request for Continued Examination in accordance with 37 CFR 1.114, where Applicant amended claims 1, 3-6, and 8 and added new claims 12-23 (the “September 8, 2026 RCE”). As such, claims 1-6, 8, and 11-23, as recited in the September 8, 2026 RCE, are currently pending and subject to the non-final office action below.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on September 8, 2026 is in compliance with the provisions of 37 CFR 1.97(b)(4), and has been considered by the examiner.
Response to Applicant’s Remarks
Response to Applicant’s Remarks Concerning Rejections under 35 U.S.C. § 112(d)
Applicant’s arguments, see Applicant’s Remarks, p. 8, Claim Rejections under 35 U.S.C. § 112(d) Section, filed September 8, 2026, with respect to rejections of claim 8 under 35 U.S.C. § 112(d) have been considered, but they are moot in light of Applicant’s amendments to claim 8. In light of the amendments to claim 8, the § 112(d) rejections are no longer necessary and are withdrawn.
Response to Applicant’s Remarks Concerning Rejections under 35 U.S.C. § 101
Applicant’s arguments, see Applicant’s Remarks, pp. 8-15, Claim Rejections under 35 U.S.C. § 101 Section, filed September 8, 2026, with respect to rejections of claim 1-6, 8, and 11 under 35 U.S.C. § 101 have been fully considered, but they are not persuasive. Further, in light of the 2019 Revised Patent Subject Matter Eligibility Guidance (available at MPEP § 2106) (the “2019 Revised PEG”), the § 101 rejections of claims 1-6, 8, and 11 are maintained and the § 101 rejections of new claims 12-23 are added in this office action.
First, Applicant argues that the claims are not directed to an abstract idea, because the claims do not merely recite a mental process. See Applicant’s Remarks, at pp. 11-12. Examiner respectfully disagrees with this argument. While the claims recite some features which are not part of an abstract mental process, particularly the steps and features directed to “collecting data from a plurality of information sources” and using a machine-learning algorithm to determine correlations among the respective information, this is not the test for determining whether the claims recite an abstract mental process. Claims can recite a mental process even if they are claimed as being performed on a computer. MPEP § 2106.04(a)(2)(III)(C). The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. Id.
Similarly, in the present case, the identified abstract idea is a computer-implemented method of detecting risk of neurodevelopmental disorders, comprising; deriving a risk level from the patient information comprising deriving and aggregating weighted individual risk assessments; and providing next-step guidance corresponding to a composite neurodevelopmental-disorder risk level. Under the broadest reasonable interpretation of the claims, these steps represent various types of observations, evaluation, judgment, and/or opinion where a person could: (1) mentally observe and detect a risk of neurodevelopmental disorders; (2) manually derive a risk level from the collected patient information including deriving and aggregating weighted individual risk assessments; and (3) mentally and manually come up with guidance based on the risk level and provide it to others. The fact that Applicant uses an electronic means to collect the patient information or a machine learning algorithm to determine one or more correlations among respective information sources amounts to merely performing the mental process in a computer environment with a machine learning algorithm. Further, claiming that the risk assessments are based on outputs from a machine-learning algorithm is claimed at a high level of generality and generally links the abstract idea to the field of machine learning, because Applicant has not described the machine-learning algorithm with any specificity, and the claims do not recite the specific steps that the machine-learning algorithm goes through in order to determine the one or more correlations among the respective information sources. Therefore, this claim limitation is recited at a high level of generality, and amounts to using a computer as a tool to perform an abstract mental process. For these reasons, this argument is not persuasive.
Next, Applicant argues that the claims provide a specific improvement in computer-related technology, because the claims “include specific techniques that may improve the efficiency associated with combining and weighting multi-modal patient data […] using a machine-learning algorithm”. Applicant’s Remarks, at p. 11. Examiner respectfully disagrees with this argument. When evaluating whether claims recite an improvement to the functioning of a computer or a technical field, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. MPEP § 2106.05(a). The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Id.
Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. An indication that the claimed invention provides an improvement can include a discussion in the specification that identifies a technical problem and explains the details of an unconventional technical solution expressed in the claim, or identifies technical improvements realized by the claim over the prior art. In the present case, Applicant has not identified a technical problem, nor has Applicant explained the details of an unconventional technical solution expressed in the claims. Specifically, the description in lines 15-19 of page 19 of Applicant’s specification, as filed on November 18, 2024, does not amount to an improvement to the functioning of a computer, technology, or technical field. For example, lines 15-19 of page 19 in Applicant’s specification merely state in a conclusory manner that the benefits and advantages of the disclosed systems and methods may be in providing timely access to accurate screening, referrals, and diagnosis in order to receive early intervention.
However, this does not represent an improvement to computer technology or a technological field; rather it amounts to stating the idea of a solution without describing the details of how that solution is accomplished. For example, the Federal Circuit held that “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. MPEP § 2106.05(f) (citing Intellectual Ventures I LLC v. Capital One Bank (USA)). Therefore, providing access to patient information “at an earlier stage” simply by collecting this information through electronic means (i.e., with generic computer devices) does not provide an improvement to the functioning of computer technology or a technological field. Still further, it is not apparent how generating correlations between information sources contributes to improving the efficiency of combining and weight patient information that is collected from different sources and ultimately used to generate individual risk assessments. As such, Applicant’s disclosed benefits amount to stating in a conclusory manner that the benefits and advantages of the disclosed systems and methods may be in providing timely access to accurate screening, referrals, and diagnosis in order to receive early intervention.
These are not technical improvements, because Applicant has not identified a technical problem that the claimed invention solves and has not identified which limitations in the claim solve such a technical problem. Rather, Applicant’s argument that the claims improve the capabilities of a computer to perform neurodevelopmental disorder risk detection amounts to stating the idea of a solution without describing the details of how that solution is accomplished. For example, in Trading Technologies Int’l v. IBG, the Federal Circuit court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology. See MPEP § 2106.05(a). Similarly, Applicant’s claims merely derive a risk level from patient information and provide guidance that corresponds to that risk level (i.e., merely displaying information in the form of the guidance that corresponds to that risk level). This does not amount to an improvement to technology or a technical field. For these reasons, this argument is not persuasive.
Lastly, Applicant generally argues that the claims provide significantly more than the exception under Step 2B, because the amended steps directed to “determining, via a machine-learning algorithm, one or more correlations among the respective information sources”; “assigning weights to the individual risk assessments based on outputs from the machine learning algorithm and the determined correlations”; and “aggregating the weighted individual risk assessments to determine a composite neurodevelopmental-disorder risk level”, goes well beyond the generic data-gathering, receiving, or transmitting functions that courts have found to be well-understood, routine, and conventional. Applicant’s Remarks, at p. 14. Examiner respectfully disagrees with this argument. When making a determination of whether the additional elements in a claim amount to significantly more than a judicial exception, the examiner should evaluate whether the elements define only well-understood, routine, conventional activity. MPEP § 2106.05(d). In this respect, the well-understood, routine, conventional consideration overlaps with other Step 2B considerations, particularly the improvement consideration (see MPEP § 2106.05(a)), the mere instructions to apply an exception consideration (see MPEP § 2106.05(f)), and the insignificant extra-solution activity consideration (see MPEP § 2106.05(g)). Id. Thus, evaluation of those other considerations may assist examiners in making a determination of whether a particular element or combination of elements is well-understood, routine, conventional activity. Id.
In the present case, the additional elements recited in the claims represent well-understood, routine, and conventional activity. Courts have held computer‐implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., manually or by merely thinking). MPEP § 2106.05(d). Applicant’s claims were deemed to recite an abstract mental process (see above). The action steps recited in the claims directed to determining one or more correlations, assigning the weights to the individual risk assessments, and aggregating the weighted individual risk assessments, can be done by human mentally or with the aid of a pen and paper, because these steps represent basic observations, evaluations, judgments, and/or opinions. Specifically, a person is mentally and/or manually capable of: (1) making some determination of the strength/relationship between types of data; (2) placing weights on the individual risk assessments; and (3) compiling the weighted aggregated risk assessments. Therefore, these steps are directed to an abstract mental process and fail to demonstrate significantly more than the abstract idea.
Therefore, Applicant’s claims do not recite any additional elements which are deemed to provide significantly more than the abstract idea. For these reasons, this argument is not persuasive. Therefore, the rejections of claims 1-6, 8, and 11 under 35 U.S.C. § 101 are maintained and the § 101 rejections of new claims 12-23 are added in this office action. Please see the amended rejections under the Claim Rejections – 35 U.S.C. § 101 Section below, for further clarification and complete analysis.
Response to Applicant’s Remarks Concerning Rejections under 35 U.S.C. § 103
Applicant’s arguments, see Applicant’s Remarks, pp. 15-20, Claim Rejections under 35 U.S.C. § 103 Section, filed September 8, 2026, with respect to rejections of claim 1-6, 8, and 11 under 35 U.S.C. § 103 have been fully considered, but they are moot in light of Applicant’s amendments to independent claims 1 and 11. Furthermore, the prior art search attached to this office action failed to generate closer prior art results. Accordingly, independent claims 1 and 11 are considered to be novel and non-obvious over the prior art. Therefore, the § 103 rejections of claims 1-6, 8, and 11 are withdrawn and claims 1-6, 8, and 11-23 are deemed to be novel and non-obvious over the prior art.
Claim Objections
Claim 20 is objected to because of the following informalities:
- In this claim, "SHAP" should be spelled out the first time it is used in the claim. Appropriate correction is required.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-6, 8, and 12-18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation “deriving individual risk assessments from respective information sources”. However, there is insufficient antecedent basis for the phrase “respective information sources” in the claim. See MPEP § 2173.05(e). The phrase “respective information sources” was not previously recited in claim 1. Examiner notes that claim 1 previously recited a step for collecting patient information from “a plurality of information sources”, however, it is generally unclear whether the plurality of information sources are the same or different than the “respective information sources” that are recited in the step for deriving the individual risk assessments. Therefore, claim 1 is indefinite for reciting a phrase that lacks antecedent basis. Examiner suggests that Applicant amend the phrase “deriving individual risk assessments from respective information sources” in claim 1 to “deriving individual risk assessments from the plurality of information sources” (i.e., amend the claims to mirror the same limitation that is recited in claim 19), or make some other appropriate correction of course. Appropriate correction is required.
Claims 2-6, 8, and 12-18 are also rejected under 35 U.S.C. § 112(b) or 35 U.S.C. § 112 (pre-AIA ), second paragraph, as being indefinite, for similar reasons as described above in the analysis of the § 112(b) rejections applied to claim 1 (due to their individual dependencies on claim 1).
Claim 5 recites the limitations "wherein extracting information from direct observation of the patient comprises […]" in lines 1 to 2 of claim 5. However, there is insufficient antecedent basis for extracting information in the claim. See MPEP § 2173.05(e). The phrase “extracting information” was not previously recited in claim 5 or in claim 1 (which claim 5 depends on). Examiner suggests that Applicant amend the phrase “wherein extracting information from direct observation of the patient comprises […]” in lines 1 to 2 of claim 5 to “wherein collecting the patient information from direct observation of the patient comprises […]”, or make some other appropriate correction of course. Appropriate correction is required.
Similarly, claim 6 recites the limitations "wherein extracting information from the phenotypic algorithm comprises […]" in lines 1 to 2 of claim 6. However, there is insufficient antecedent basis for extracting information in the claim. See MPEP § 2173.05(e). The phrase “extracting information” was not previously recited in claim 6 or in claim 1 (which claim 6 depends on). Examiner suggests that Applicant amend the phrase “wherein extracting information from the phenotypic algorithm comprises […]” in lines 1 to 2 of claim 6 to “wherein collecting the patient information from the phenotypic algorithm comprises […]”, or make some other appropriate correction of course. Appropriate correction is required.
Claims 8 and 18 recite the limitation “behavioral-testing information” in line 4 of claim 8 and line 2 of claim 18. However, there is insufficient antecedent basis for behavioral-testing information in the claim. See MPEP § 2173.05(e). The phrase “behavioral-testing information” was not previously recited in either of claims 8 or 18, nor was it previously recited in claim 1 (which claims 8 and 18 individually depend on). Therefore, it is generally unclear what information Applicant is referring to in claims 8 and 18 when Applicant recites “behavioral-testing information” in those dependent claims. As such, claims 8 and 18 are indefinite for reciting a term that lacks antecedent basis. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-6, 8, and 11-23 are rejected under 35 U.S.C. §101 because the claimed invention is directed to an abstract idea without significantly more. See MPEP § 2106 (hereinafter referred to as the “2019 Revised PEG”).
Step 1 of the 2019 Revised PEG
Following Step 1 of the 2019 Revised PEG, claims 1-6, 8, and 12-18 are directed to a computer-implemented method of detecting risk of neurodevelopmental disorders, which is within one of the four statutory categories (i.e., a process). See MPEP § 2106.03. Claim 11 are directed to a system for detecting and/or monitoring risk of neurodevelopmental disorders, which is also within one of the four statutory categories (i.e., a machine or apparatus). See id. Claims 19-23 are also directed to a system for detecting and monitoring risk of neurodevelopmental disorders, which is also within one of the four statutory categories (i.e., a machine or apparatus). See id.
Step 2A of the 2019 Revised PEG - Prong One
Following Prong One of Step 2A of the 2019 PEG, the claim limitations are to be analyzed to determine whether they “recite” a judicial exception or in other words whether a judicial exception is “set forth” or “described” in the claims. See MPEP §2106.04. An “abstract idea” judicial exception is subject matter that falls within at least one of the following groupings: (1) Mathematical Concepts; (2) Certain Methods of Organizing Human Activity, and (3) Mental Processes. See MPEP § 2106.04(a).
Claims 1-6, 8, and 11-23 are rejected under 35 U.S.C. § 101, because the claimed invention is directed to an abstract idea without significantly more. Representative independent claims 1, 11, and 19 include limitations that recite an abstract idea. Note that independent claim 1 is a method, while claim 11 covers the matching system and claim 19 covers a similar system. Specifically, independent claim 1 recites the following limitations:
A computer-implemented method of detecting risk of neurodevelopmental disorders, the method comprising:
collecting patient information from a plurality of information sources comprising: an electronically-administered screening survey, electronic health records information; direct observation of the patient via an application delivered on a computer, tablet, or smartphone; a phenotypic algorithm that is based on active closed-loop sensing, wherein the patient is shown brief, developmentally-appropriate, dynamic stimuli on a device while sensors on the device capture information for automatic, objective quantification of several behavioral risk markers; one or more predictive markers; and genetic testing selected from the group consisting of chromosomal microarray analysis, exome and/or whole genome sequencing, and testing designed to detect point mutations, or any combination thereof;
deriving individual risk assessments from respective information sources;
determining, via a machine-learning algorithm, one or more correlations among the respective information sources;
assigning weights to the individual risk assessments based on outputs from the machine learning algorithm and the determined correlations;
aggregating the weighted individual risk assessments to determine a composite neurodevelopmental-disorder risk level;
generating a prediction confidence value associated with the composite neurodevelopmental-disorder risk level;
generating a quality value indicating whether an assessment should be readministered; and
providing next-step guidance corresponding to the composite neurodevelopmental-disorder risk level by interfacing with a central healthcare data system to deliver recommendations for referrals, treatment, caregiver strategies, monitoring, or any combination thereof.
Similarly, independent claim 19 recites the following limitations:
A system for detecting and monitoring risk of neurodevelopmental disorders, comprising:
a computing platform including one or more processors and memory storing instructions that when executed cause the computing platform to:
collect patient information from a plurality of information sources including an electronically-administered screening survey, electronic health record information, direct observation information, phenotypic algorithm information, predictive markers, and genetic testing information;
derive individual risk assessments from the plurality of information sources;
determine correlations among the information sources using a machine-learning algorithm;
assign weights to the individual risk assessments based on machine-learning outputs and the determined correlations;
aggregate the weighted individual risk assessments to determine a composite neurodevelopmental-disorder risk level;
generate a prediction confidence value and a quality value associated with the composite neurodevelopmental-disorder risk level; and
determine whether the prediction confidence value satisfies a threshold confidence level; and
responsive to the prediction confidence value failing to satisfy the threshold confidence level, indicate that the quality value indicating that the assessment should be readministered.
However, the Examiner submits that the foregoing underlined limitations constitute a process that, under its broadest reasonable interpretation, falls within the “Mental Processes” grouping of abstract ideas. See MPEP § 2106.04(a)(2)(III). The Mental Processes category covers concepts which are capable of being performed in the human mind or encompasses a human performing the step(s) mentally with the aid of a pen and paper (including an observation, evaluation, judgment, or opinion) (i.e., a method of detecting risk of neurodevelopmental disorders, comprising; deriving individual risk assessments from respective information sources; determining one or more correlations among the respective information sources; assigning weights to the individual risk assessments; aggregating the weighted individual risk assessments to determine a composite neurodevelopmental-disorder risk level; generating a prediction confidence value and a quality value; providing next-step guidance corresponding to the composite neurodevelopmental-disorder risk level [or determining whether the prediction confidence value satisfies a threshold confidence level and responsive to the prediction confidence value failing to satisfy the threshold confidence level, indicating that the quality value indicating that the assessment should be readministered]). See MPEP § 2106.04(a)(2)(III). That is, other than reciting some computer components and functions (the foregoing limitations in claim 1 which are not underlined), the context of claims 1, 11, and 19 encompasses concepts that are capable of being performed in the human mind or encompasses a human performing the step(s) mentally with the aid of a pen and paper (including an observation, evaluation, judgment, and/or opinion) (i.e., a method of detecting risk of neurodevelopmental disorders, comprising; deriving individual risk assessments from respective information sources; determining one or more correlations among the respective information sources; assigning weights to the individual risk assessments; aggregating the weighted individual risk assessments to determine a composite neurodevelopmental-disorder risk level; generating a prediction confidence value and a quality value; and providing next-step guidance corresponding to the composite neurodevelopmental-disorder risk level [or determining whether the prediction confidence value satisfies a threshold confidence level and responsive to the prediction confidence value failing to satisfy the threshold confidence level, indicating that the quality value indicating that the assessment should be readministered]).
The aforementioned claim limitations described in claims 1, 11, and 19 are analogous to claim limitations directed toward concepts which are capable of being performed in the human mind or encompasses a human performing the step(s) mentally with the aid of a pen and paper, because they represent different types of observations, evaluations, judgments, and/or opinions. As an example, a medical professional could practically in their mind and/or with the aid of a pen and paper: (1) detect a risk of neurodevelopmental disorders (i.e., a type of observation, evaluation, judgment, and/or opinion where a person could mentally observe and detect a risk of neurodevelopmental disorders); (2) derive individual risk assessments from respective information sources (i.e., a type of observation, evaluation, judgment, and/or opinion where a person could manually derive individual risk assessments); (3) determine one or more correlations among the respective information sources (i.e., a type of observation, evaluation, judgment, and/or opinion where a person could mentally and/or determine correlations between different types of data); (4) assign weights to the individual risk assessments (i.e., a type of observation, evaluation, judgment, and/or opinion where a person could manually assign weights to risk assessments); (5) aggregate the weighted individual risk assessments to determine a composite neurodevelopmental-disorder risk level (i.e., a type of observation, evaluation, judgment, and/or opinion where a person could manually aggregate data); (6) generate a prediction confidence value and a quality value (i.e., a type of observation, evaluation, judgment, and/or opinion where a person could mentally generate confidence and quality values for certain data); and (7) provide next-step guidance corresponding to the composite neurodevelopmental-disorder risk level (i.e., a type of observation, evaluation, judgment, and/or opinion where a person could mentally and manually come up with guidance based on the risk level and provide it to others).
Further, Applicant’s claims are similar to claims which have been held to recite an abstract mental process. For example, the Federal Circuit held that a claim directed to “collecting information, analyzing it, and displaying certain results of the collection and analysis”, where the data analysis steps are recited at a high level of generality amounted to steps that could practically be performed in the human mind. See MPEP § 2106.04(a)(2)(III)(A) (citing Electric Power Group v. Alstom, S.A.). Similarly, Applicant’s claims recite steps for collecting information (i.e., the step directed to collecting patient information); analyzing the data (i.e., deriving the individual risk assessments; determining the correlations between the information sources; and aggregating individual risk assessments); and displaying certain results about the collection and analysis (i.e., providing next-step guidance based on the risk level), at a high level of generality. Therefore, the aforementioned underlined claim limitations may reasonably be interpreted as mental/manual observations, evaluations, judgments, and/or opinions made by a person, such as healthcare provider. If a claim limitation, under its broadest reasonable interpretation, covers concepts which are capable of being performed in the human mind or encompasses a human performing the step(s) mentally with the aid of a pen and paper, then it falls within the “Mental Processes” grouping of abstract ideas. See MPEP § 2106.04(a)(2)(III). Accordingly, claims 1, 11, and 19 recite an abstract idea that falls within the Mental Processes category.
Furthermore, Examiner notes that dependent claims 2, 12-15, 17, 18, 21, and 22 further defines and limits the at least one abstract idea (and thus fail to make the abstract idea any less abstract) as set forth below. Examiner notes that: (1) dependent claims 3-6, 8, 16, 20, and 23 include limitations that are deemed to be additional elements, and require further analysis under Prong Two of Step 2A; and (2) dependent claims 2, 12-15, 17, 18, 21, and 22 does not provide any limitations that are deemed to be additional elements which require further analysis under Prong Two of Step 2A.
- For example, claim 2 further defines and limits the abstract idea recited in claim 1 by merely reciting that the predictive markers comprise patterns of early medical conditions (i.e., this step is deemed to be reasonably performed mentally, because it further modifies the collected patient data).
- Similarly, claims 12-15 further limit the abstract idea by reciting other mental steps, such as, determining whether the confidence values satisfy a threshold, providing recommendations for additional testing as part of the next-step guidance, and limiting the type of behavior risk markers that are collected in order to make the determinations in the independent claims (i.e., this step is deemed to be reasonably performed mentally, because it further modifies the collected patient data).
- Claim 17 calls for the quality value indicating whether the assessment should be re-administered when one or more assessment metrics are insufficient for an accurate assessment (i.e., this step is deemed to be reasonably performed mentally, because it is an example of an observation, evaluation, judgment, and/or opinion made by a person).
- Claim 18 calls for the ML algorithm identifying correlations among behavioral-testing information, screening information, electronic health record information, and genetic-testing information (i.e., this step is deemed to be reasonably performed mentally, because it is an example of an observation, evaluation, judgment, and/or opinion made by a person).
- Claim 21 calls for the computing platform being capable of accounting for differences in the number of information sources available for different patients when generating the composite neurodevelopmental-disorder risk level (i.e., this step is deemed to be reasonably performed mentally, because it is an example of an observation, evaluation, judgment, and/or opinion made by a person).
- Claim 22 calls for the computing platform being capable of quantifying behavioral risk markers comprising patterns of attention, gaze, orienting, facial movements, facial expressions, oral kinetics, posture, touch, blink rate, motor responses, or combinations thereof (i.e., this step is deemed to be reasonably performed mentally, because it is an example of an observation, evaluation, judgment, and/or opinion made by a person).
Step 2A of the 2019 Revised PEG - Prong Two
Regarding Prong Two of Step 2A of the 2019 Revised PEG, it must be determined whether the claim as a whole integrates the abstract idea into a practical application. As noted in the 2019 Revised PEG, it must be determined whether any additional elements in the claims are indicative of integrating the abstract idea into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” See MPEP §§ 2106.05 (f)-(h).
In the present case, for independent claims 1 and 11, the additional limitations beyond the above-noted at least one abstract idea are as follows (where the bolded portions are the “additional limitations” while the underlined portions continue to represent the at least one “abstract idea”):
A computer-implemented (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)) method of detecting risk of neurodevelopmental disorders, the method comprising::
collecting patient information from a plurality of information sources comprising: an electronically-administered screening survey, electronic health records information; direct observation of the patient via an application delivered on a computer, tablet, or smartphone; a phenotypic algorithm that is based on active closed-loop sensing, wherein the patient is shown brief, developmentally-appropriate, dynamic stimuli on a device while sensors on the device capture information for automatic, objective quantification of several behavioral risk markers; one or more predictive markers; and genetic testing selected from the group consisting of chromosomal microarray analysis, exome and/or whole genome sequencing, and testing designed to detect point mutations, or any combination thereof (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); the Examiner submits that this additional element amounts to adding insignificant extra-solution activity as noted below, see MPEP § 2106.05(g); and the Examiner further submits that such steps are not unconventional as they merely consist of receiving data over a network, as evidenced by the Intellectual Ventures v. Symantec case, as noted below in the Step 2B Analysis Section, see MPEP § 2106.05(d));
deriving individual risk assessments from respective information sources;
determining, via a machine-learning algorithm (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); and the Examiner further submits that this additional element amounts to generally linking the abstract idea to a particular field of use or technological environment as noted below, see MPEP § 2106.05(h)), one or more correlations among the respective information sources;
assigning weights to the individual risk assessments based on outputs from the machine learning algorithm (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); and the Examiner further submits that this additional element amounts to generally linking the abstract idea to a particular field of use or technological environment as noted below, see MPEP § 2106.05(h)) and the determined correlations;
aggregating the weighted individual risk assessments to determine a composite neurodevelopmental-disorder risk level;
generating a prediction confidence value associated with the composite neurodevelopmental-disorder risk level;
generating a quality value indicating whether an assessment should be readministered; and
providing next-step guidance corresponding to the composite neurodevelopmental-disorder risk level by interfacing with a central healthcare data system (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)) to deliver recommendations for referrals, treatment, caregiver strategies, monitoring, or any combination thereof; and
a computer system (as described in claim 11) (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)).
Similarly, for independent claim 19, the additional limitations beyond the above-noted at least one abstract idea are as follows (where the bolded portions are the “additional limitations” while the underlined portions continue to represent the at least one “abstract idea”):
A system (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)) for detecting and monitoring risk of neurodevelopmental disorders, comprising:
a computing platform including one or more processors and memory storing instructions that when executed cause the computing platform to (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)):
collect patient information from a plurality of information sources including an electronically-administered screening survey, electronic health record information, direct observation information, phenotypic algorithm information, predictive markers, and genetic testing information (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); the Examiner submits that this additional element amounts to adding insignificant extra-solution activity as noted below, see MPEP § 2106.05(g); and the Examiner further submits that such steps are not unconventional as they merely consist of receiving data over a network, as evidenced by the Intellectual Ventures v. Symantec case, as noted below in the Step 2B Analysis Section, see MPEP § 2106.05(d));
derive individual risk assessments from the plurality of information sources;
determine correlations among the information sources using a machine-learning algorithm (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); and the Examiner further submits that this additional element amounts to generally linking the abstract idea to a particular field of use or technological environment as noted below, see MPEP § 2106.05(h));
assign weights to the individual risk assessments based on machine-learning outputs (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); and the Examiner further submits that this additional element amounts to generally linking the abstract idea to a particular field of use or technological environment as noted below, see MPEP § 2106.05(h)) and the determined correlations;
aggregate the weighted individual risk assessments to determine a composite neurodevelopmental-disorder risk level;
generate a prediction confidence value and a quality value associated with the composite neurodevelopmental-disorder risk level; and
determine whether the prediction confidence value satisfies a threshold confidence level; and
responsive to the prediction confidence value failing to satisfy the threshold confidence level, indicate that the quality value indicating that the assessment should be readministered.
However, the recitation of these generic computer components and functions in claims 1, 11, and 19 are recited at a high-level of generality (i.e., using a generic computer device to perform the abstract idea of: a method of detecting risk of neurodevelopmental disorders, comprising; deriving individual risk assessments from respective information sources; determining one or more correlations among the respective information sources; assigning weights to the individual risk assessments; aggregating the weighted individual risk assessments to determine a composite neurodevelopmental-disorder risk level; generating a prediction confidence value and a quality value; and providing next-step guidance corresponding to the composite neurodevelopmental-disorder risk level [or determining whether the prediction confidence value satisfies a threshold confidence level and responsive to the prediction confidence value failing to satisfy the threshold confidence level, indicating that the quality value indicating that the assessment should be readministered]), such that it amounts to no more than: (1) adding the words “apply it” (or is the equivalent of) with the judicial exception; mere instructions to implement an abstract idea on a computer; or merely uses a computer as a tool to perform an abstract idea; (2) adding insignificant extra-solution activity to the judicial exception; and (3) generally linking the use of a judicial exception to a particular technological environment or field of use. See MPEP §§ 2106.05(f)-(h). For the following reasons, the Examiner submits that the above identified additional limitations do not integrate the above-noted at least one abstract idea into a practical application.
- The following is an example of court decisions that demonstrate merely applying instructions by reciting the computer structure as a tool to implement the claimed limitations (e.g., see MPEP § 2106.05(f)):
- A commonplace business method or mathematical algorithm being applied on a general purpose computer, e.g., see Alice Corp. Pty. Ltd. v. CLS Bank Int’l – similarly, the current invention implements the commonplace risk detection method on a generic computing device (i.e., the Examiner submits that the additional elements directed to the computer, tablet, or smartphone, and the computing system, are the equivalent of general purpose computer devices).
- Requiring the use of software to tailor information and provide it to the user on a generic computer, e.g., see Intellectual Ventures I LLC v. Capital One Bank (USA) – similarly, the current invention requires configuring the computing system (i.e., where the instructions on the computing platform; the application delivered on the computer, tablet, or smartphone; and the step of configuring the computing system, are deemed to be the equivalent of implementing generic software) to perform the abstract idea.
- The following is an example of an insignificant extra-solution activity (e.g., see MPEP § 2106.05(g)):
- Example of Mere Data Gathering/Mere Data Outputting:
- Obtaining information about transactions using the Internet to verify credit card transactions, e.g., see CyberSource v. Retail Decisions, Inc. – similarly, the steps directed to: “collecting patient information from an electronically-administered screening survey, electronic health records information; direct observation of the patient via an application delivered on a computer, tablet, or smartphone; a phenotypic algorithm that is based on active closed-loop sensing, wherein the patient is shown brief, developmentally-appropriate, dynamic stimuli on a device while sensors on the device capture information for automatic, objective quantification of several behavioral risk markers; one or more predictive markers; and genetic testing selected from the group consisting of chromosomal microarray analysis, exome and/or whole genome sequencing, and testing designed to detect point mutations; or any combination thereof”, described in claims 1 and 11 and similarly described in claim 19, are a necessary data gathering steps (i.e., collecting the information from the one or more information sources is a necessary data gathering step in order to derive the individual risk assessments.).
- The following are examples of generally linking the use of a judicial exception to a particular technological environment or field of use (e.g., see MPEP § 2106.05(h)):
- (1) Specifying that the abstract idea of monitoring audit log data relates to transactions or activities that are executed in a computer environment, because this requirement merely limits the claims to the computer field, i.e., to execution on a generic computer, FairWarning v. Iatric Sys.; (2) Specifying that the abstract idea of using advertising as currency is used on the Internet, because this narrowing limitation is merely an attempt to limit the use of the abstract idea to a particular technological environment, Ultramercial, Inc. v. Hulu; and (3) Requiring that the abstract idea of creating a contractual relationship that guarantees performance of a transaction (a) be performed using a computer that receives and sends information over a network, or (b) be limited to guaranteeing online transactions, because these limitations simply attempted to limit the use of the abstract idea to computer environments, buySAFE Inc. v. Google, Inc. - similarly, the limitations directed to “a machine-learning algorithm” and “based on outputs from the machine learning algorithm”, amounts to limiting the abstract idea to the field of machine learning models/algorithms. See MPEP § 2106.05(h).
Thus, the additional elements in independent claims 1, 11, and 19 are not indicative of integrating the judicial exception into a practical application. Similarly, dependent claims 2, 12-15, 17, 18, 21, and 22 does not recite any additional elements outside of those identified as being directed to the abstract idea described above. Examiner notes that dependent claims 3-6, 8, 16, 20, and 23 recite the following additional elements identified in bold font below (with limitations deemed to be part of the above identified abstract idea identified in underlined font):
wherein the machine learning algorithm is used (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); and the Examiner further submits that this additional element amounts to generally linking the abstract idea to a particular field of use or technological environment as noted below, see MPEP § 2106.05(h)) to identify the predictive markers (as described in claim 3);
wherein the machine learning algorithm comprises a transformer-based neural network pre-trained on biomedical text (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); and the Examiner further submits that this additional element amounts to generally linking the abstract idea to a particular field of use or technological environment as noted below, see MPEP § 2106.05(h)) (as described in claim 4);
wherein extracting information from direct observation of the patient comprises: observing the patient via the application using computer vision analysis (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); and the Examiner further submits that this additional element amounts to generally linking the abstract idea to a particular field of use or technological environment as noted below, see MPEP § 2106.05(h)); and transmitting the patient information from the computer, tablet, or smartphone to the central healthcare data system (the Examiner submits that this additional element amounts to adding insignificant extra-solution activity as noted below, see MPEP § 2106.05(g); and the Examiner further submits that such steps are not unconventional as they merely consist of receiving data over a network, as evidenced by the Intellectual Ventures v. Symantec case, as noted below in the Step 2B Analysis Section, see MPEP § 2106.05(d)) (as described in claim 5);
wherein extracting information from the phenotypic algorithm comprises collecting data from computer vision analysis of activities selected from the group consisting of response to name, facial expression and dynamics, postural control and fine motor skills, social attention, and any combination thereof (the Examiner submits that this additional element amounts to adding insignificant extra-solution activity as noted below, see MPEP § 2106.05(g); and the Examiner further submits that such steps are not unconventional as they merely consist of receiving data over a network, as evidenced by the Intellectual Ventures v. Symantec case, as noted below in the Step 2B Analysis Section, see MPEP § 2106.05(d)) (as described in claim 6);
wherein assigning weights to the individual risk assessments based on outputs from a machine learning algorithm (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f); and the Examiner further submits that this additional element amounts to generally linking the abstract idea to a particular field of use or technological environment as noted below, see MPEP § 2106.05(h)) comprises assigning different weights to genetic-testing information and behavioral-testing information (as described in claim 8);
wherein the behavioral risk markers are automatically quantified using sensor data captured while the patient is presented with developmentally appropriate dynamic stimuli (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)) (as described in claim 16);
wherein the computing platform stores machine-learning algorithms and SHAP analysis logic for determining contributions of individual information sources to the composite neurodevelopmental-disorder risk level (the Examiner submits that this additional element amounts to adding insignificant extra-solution activity as noted below, see MPEP § 2106.05(g); and the Examiner further submits that such steps are not unconventional as they merely consist of storing and retrieving information in memory, as evidenced by the Versata Dev. Group, Inc. v. SAP Am., Inc. case, as noted below in the Step 2B Analysis Section, see MPEP § 2106.05(d)) (as described in claim 20); and
wherein the patient information is collected by obtaining, via the computer platform, behavioral-response data (the Examiner submits that this additional element amounts to adding insignificant extra-solution activity as noted below, see MPEP § 2106.05(g); and the Examiner further submits that such steps are not unconventional as they merely consist of receiving data over a network, as evidenced by the Intellectual Ventures v. Symantec case, as noted below in the Step 2B Analysis Section, see MPEP § 2106.05(d)) by: presenting developmentally-appropriate dynamic stimuli to a patient (the Examiner submits that this additional element amounts to adding insignificant extra-solution activity as noted below, see MPEP § 2106.05(g); and the Examiner further submits that such steps are not unconventional as they merely consist of receiving data over a network, as evidenced by the Intellectual Ventures v. Symantec case, as noted below in the Step 2B Analysis Section, see MPEP § 2106.05(d)); capturing, via one or more sensors of the computing platform, behavioral-response information generated in response to the stimuli (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)); and automatically quantifying, by the computing platform, behavioral risk markers from the behavioral-response information (the Examiner submits that this additional element amounts to adding the words “apply it” (or an equivalent), or mere instructions to implement the abstract idea on a computer, see MPEP § 2106.05(f)) (as described in claim 23).
As such, the additional elements in claims 1, 3-6, 8, 11, 16, 19, 20, and 23 are not indicative of integrating the judicial exception into a practical application. Looking at the additional limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For instance, unlike the claims that have been held as a whole to be directed to an improvement or otherwise directed to something more than the abstract idea, claims 1-6, 8, and 11-23: (1) are not directed to improvements to the functioning of a computer, or to any other technology or technical field similar to the Enfish, LLC v. Microsoft Corp. case (see MPEP § 2106.05(a)); (2) do not apply or use a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition (see MPEP § 2106.04(d)(2)); (3) do not apply the judicial exception with, or by use of, a particular machine (see MPEP § 2106.05(b)); (4) do not effect a transformation or reduction of a particular article to a different state or thing (see MPEP § 2106.05(c)); nor do they (5) apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as whole is more than a drafting effort designed to monopolize the exception (see MPEP § 2106.05(e) and MPEP § 2106.04(d)(2)). For these reasons, claims 1-6, 8, and 11-23 do not recite additional elements that integrate the judicial exception into a practical application.
Step 2B of the 2019 Revised PEG
Regarding Step 2B of the 2019 Revised PEG, claims 1-6, 8, and 11-23 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, with respect to integration of abstract idea into a practical application, the additional elements of claims 1, 3-6, 8, and 11-23 amount to no more than: (1) adding the words “apply it” (or is the equivalent of) with the judicial exception; mere instructions to implement an abstract idea on a computer; or merely uses a computer as a tool to perform an abstract idea; (2) adding insignificant extra-solution activity to the judicial exception; and (3) generally linking the use of a judicial exception to a particular technological environment or field of use. See MPEP §§ 2106.05(f)-(h). Further the additional elements, other than the abstract idea per se, when considered both individually and as an ordered combination, amount to no more than limitations consistent with what the courts recognize, or those having ordinary skill in the art would recognize, to be well-understood, routine, and conventional computer components. See MPEP § 2106.05 (d).
Specifically, the Examiner submits that the additional elements of claims 1, 3-6, 8, and 11-23, as recited, the system; computing platform; one or more processors; memory storing instructions; computing system; application delivered on a computer, tablet, or smartphone; machine learning algorithm; machine learning algorithm comprising a transformer-based neural network pre-trained on biomedical text; application using computer vision analysis; and the steps directed to: “collecting patient information from a plurality of information sources comprising: an electronically-administered screening survey, electronic health records information; direct observation of the patient via an application delivered on a computer, tablet, or smartphone; a phenotypic algorithm that is based on active closed-loop sensing, wherein the patient is shown brief, developmentally-appropriate, dynamic stimuli on a device while sensors on the device capture information for automatic, objective quantification of several behavioral risk markers; one or more predictive markers; and genetic testing selected from the group consisting of chromosomal microarray analysis, exome and/or whole genome sequencing, and testing designed to detect point mutations, or any combination thereof”; “based on outputs from a machine learning algorithm”; “by interfacing with a central healthcare data system”; “transmitting the patient information from the computer, tablet, or smartphone to the central healthcare data system”; “wherein extracting information from the phenotypic algorithm comprises collecting data from computer vision analysis of activities selected from the group consisting of response to name, facial expression and dynamics, postural control and fine motor skills, social attention, and any combination thereof”; “wherein the behavioral risk markers are automatically quantified using sensor data captured while the patient is presented with developmentally appropriate dynamic stimuli”; “wherein the computing platform stores machine-learning algorithms and SHAP analysis logic for determining contributions of individual information sources to the composite neurodevelopmental-disorder risk level”; “wherein the patient information is collected by obtaining, via the computer platform, behavioral-response data”; “presenting developmentally-appropriate dynamic stimuli to a patient”; “capturing, via one or more sensors of the computing platform, behavioral-response information generated in response to the stimuli”; and “automatically quantifying, by the computing platform, behavioral risk markers from the behavioral-response information”, are well-understood, routine, and conventional functions. See MPEP § 2106.05(d)(II).
- In regard to the system; computing platform; one or more processors; memory storing instructions; computing system; application delivered on a computer, tablet, or smartphone; machine learning algorithm; machine learning algorithm comprising a transformer-based neural network pre-trained on biomedical text; application using computer vision analysis; and the steps directed to: “based on outputs from a machine learning algorithm”; “by interfacing with a central healthcare data system”; “wherein the behavioral risk markers are automatically quantified using sensor data captured while the patient is presented with developmentally appropriate dynamic stimuli”; “capturing, via one or more sensors of the computing platform, behavioral-response information generated in response to the stimuli”; and “automatically quantifying, by the computing platform, behavioral risk markers from the behavioral-response information”, these additional elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than well-understood, routine, and conventional activities previously known to the industry, because:
- Applicant’s disclosure supports this assertion. For example, Applicant discloses that the system may comprise any suitable elements necessary configured to perform the disclosed method, such as “a computer having a processor and a memory configured to execute the algorithms and user interface device(s) such as a tablet, smartphone, camera, video display, etc.” (see Applicant’s substitute specification as filed on November 18, 2024, p. 8, lines 25-31). These passages in Applicant’s specification indicate that the system is conventional in nature (i.e., well-understood, routine, and conventional computer devices and software). Therefore, the Examiner submits that these additional elements represent well-understood, routine, and conventional computer devices and functions which are known in the medical industry.
- The Examiner submits that these limitations amount to merely using a computer or other machinery as tools for performing their typical functionality in conjunction with performing the above-noted at least one abstract idea (see MPEP § 2106.05(f) and analysis of these limitations under Step 2A, Prong Two above).
- The Examiner submits that these limitations generally link the use of the judicial exception to a particular technological environment or field of use – for example, the machine learning algorithm; and the limitations directed to: “based on outputs from a machine learning algorithm”; “the machine learning algorithm comprising a transformer-based neural network pre-trained on biomedical text”; and “the application using computer vision analysis”, amount to limiting the abstract idea to the fields of machine learning and computer vision analysis technologies (see MPEP § 2106.05(h) and analysis of these limitations under Step 2A, Prong Two above).
Therefore, these limitations are also deemed to be well-understood, routine, and conventional under Step 2B for similar reasons since they are claimed in a generic manner.
- Regarding the steps and features directed to: the steps directed to: “collecting patient information from a plurality of information sources comprising: an electronically-administered screening survey, electronic health records information; direct observation of the patient via an application delivered on a computer, tablet, or smartphone; a phenotypic algorithm that is based on active closed-loop sensing, wherein the patient is shown brief, developmentally-appropriate, dynamic stimuli on a device while sensors on the device capture information for automatic, objective quantification of several behavioral risk markers; one or more predictive markers; and genetic testing selected from the group consisting of chromosomal microarray analysis, exome and/or whole genome sequencing, and testing designed to detect point mutations, or any combination thereof”; “transmitting the patient information from the computer, tablet, or smartphone to the central healthcare data system”; “wherein extracting information from the phenotypic algorithm comprises collecting data from computer vision analysis of activities selected from the group consisting of response to name, facial expression and dynamics, postural control and fine motor skills, social attention, and any combination thereof”; “wherein the computing platform stores machine-learning algorithms and SHAP analysis logic for determining contributions of individual information sources to the composite neurodevelopmental-disorder risk level”; “wherein the patient information is collected by obtaining, via the computer platform, behavioral-response data”; and “presenting developmentally-appropriate dynamic stimuli to a patient” - The following represents examples that courts have identified to be well-understood, routine, and conventional activities (e.g., see MPEP § 2106.05(d)):
- Receiving or transmitting data over a network, e.g., see Intellectual Ventures v. Symantec – similarly the limitations directed to: “collecting patient information from a plurality of information sources comprising: an electronically-administered screening survey, electronic health records information; direct observation of the patient via an application delivered on a computer, tablet, or smartphone; a phenotypic algorithm that is based on active closed-loop sensing, wherein the patient is shown brief, developmentally-appropriate, dynamic stimuli on a device while sensors on the device capture information for automatic, objective quantification of several behavioral risk markers; one or more predictive markers; and genetic testing selected from the group consisting of chromosomal microarray analysis, exome and/or whole genome sequencing, and testing designed to detect point mutations, or any combination thereof”; “transmitting the patient information from the computer, tablet, or smartphone to the central healthcare data system”; “wherein extracting information from the phenotypic algorithm comprises collecting data from computer vision analysis of activities selected from the group consisting of response to name, facial expression and dynamics, postural control and fine motor skills, social attention, and any combination thereof”; “wherein the patient information is collected by obtaining, via the computer platform, behavioral-response data”; and “presenting developmentally-appropriate dynamic stimuli to a patient”, are similarly deemed to be well-understood, routine, and conventional activity in the medical field, because they also represent the mere collection and transmission of data over a network (i.e., the aforementioned limitations are each the equivalent of receiving and transmitting patient information over a network). See MPEP § 2106.05(d).
- Storing and retrieving information in memory, e.g., see Versata Dev. Group, Inc. v. SAP Am., Inc. – similarly the limitations directed to: “wherein the computing platform stores machine-learning algorithms and SHAP analysis logic for determining contributions of individual information sources to the composite neurodevelopmental-disorder risk level”, are similarly deemed to be well-understood, routine, and conventional activity in the medical field, because they also represent the storage of data in a memory or storage device. See MPEP § 2106.05(d).
Therefore, the additional elements described in claims 1, 3-6, 8, 11, 16, 19, 20, and 23 are deemed to be additional elements which do not amount to significantly more than the abstract idea identified above.
Thus, taken alone, the additional elements of claims 1, 3-6, 8, 11, 16, 19, 20, and 23 do not amount to significantly more than the above-identified judicial exception (the abstract idea). Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functionality of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation. Therefore, whether taken individually or as an ordered combination, claims 1, 3-6, 8, 11, 16, 19, 20, and 23 are nonetheless rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter.
Additionally, dependent claims 2, 12-15, 17, 18, 21, and 22 (which individually depend on claims 1 and 19), do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Examiner notes that dependent claims 2, 12-15, 17, 18, 21, and 22 do not include any additional elements beyond those identified as well-understood, routine, and conventional components as described above in the subject matter eligibility rejections of independent claims 1 and 19. Dependent claims 2, 12-15, 17, 18, 21, and 22 merely adds limitations that further narrow the abstract idea described in independent claims 1 and 19. Therefore, claims 1-6, 8, and 11-23 are nonetheless rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See PTO-892.
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/N.A.A./Examiner, Art Unit 3686
/JONATHON A. SZUMNY/Primary Examiner, Art Unit 3686
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