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 .
Response to Amendments
The amendment and response filed on June 5, 2025, to the Non-Final Office Action dated March 5, 2025 has been entered. Claims 1, 3, 6-8, 11, 13, and 15 are amended; Claim 14 is cancelled; and Claims 16-20 have been added. Claims 1 – 13 and 15-20 are pending in this application.
Response to Arguments
Applicant’s arguments and amendments, see pages 11-16, filed May 09, 2022, with respect to the 35 U.S.C. § 101 rejection have been considered and are non-persuasive. The 35 U.S.C. § 101 rejection of claims 1-13 and 15 (now claims 1-3 and 15-20) is maintained for the reasons explained below.
Applicant primarily asserts two arguments (i) the claim contains limitation that cannot be performed by the human mind; and (ii) there is integration of the abstract subject matter because it improves a technical field, i.e., the technical of medicine is being improved.
As to the first argument, the examiner disagrees that merely including a generic “processor” as the means for performing data gathering and calculation is sufficient to cause a claim to be statutory. See Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94 (Fed. Cir. 2015) ("Just as Diehr could not save the claims in Alice, which were directed to ‘implement[ing] the abstract idea of intermediated settlement on a generic computer’, it cannot save OIP's claims directed to implementing the abstract idea of price optimization on a generic computer."). Merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection.
As to the second argument, the field of medicine is not recited in the claims or applicant’s specification so it is not apparent how the field of medicine is being improved. The claims are drawn to generating a predictive model and for applying the predictive model to select a postoperative bed type. A model or improvement of a model is generally not within the protected class of invention. See Parker v. Flook, 437 U.S. 584 (1978); and Recentive Analytics, Inc. v. Fox Corp., No. 23-2437 (Fed. Cir. Apr. 18, 2025)(“Today, we hold only that patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under § 101.” ).
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 1-13 and 15-20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The determination of whether a claim recites patent ineligible subject matter is a 2 step inquiry.
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), see MPEP 2106.03, or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis: see MPEP 2106.04
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon? see MPEP 2106.04(II)(A)(1)
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? see MPEP 2106.04(II)(A)(2)
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? see MPEP 2106.05
101 Analysis – Step 1
Claim 1 is directed to a system for generating a predictive model (i.e., an apparatus). Therefore, claim 1 is within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. see MPEP 2106(A)(II)(1) and MPEP 2106.04(a)-(c)
Independent claim 1 includes limitations that recite an abstract idea (emphasized below [with the category of abstract idea in brackets]) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites:
1. A system for generating a predictive model for predicting a postoperative bed type for use by a patient after surgery, comprising:
an input interface for accessing medical data comprising records of surgeries, wherein a record of a surgery is indicative of a postoperative bed type used by a patient after the surgery, wherein the postoperative bed type is one of at least two possible bed types, wherein the medical data comprises data characterizing the surgery and the patient;
a processor subsystem configured to generate a predictive model for predicting the postoperative bed type to be used by a patient after surgery the processor subsystem configured to:
identify, in the medical data, a set of features relevant for prediction of the postoperative bed type in particular field of the surgery;
training a predictive model on the medical data, wherein the training uses the postoperative bed type as prediction target, wherein the predictive model is configured to output a probability on a scale which corresponds to, at its lower end, a prediction of a first one of the at least two possible bed types and, at its upper end, a prediction of a second one of the at least two possible bed types [Mental process and Mathematical Algorithm];
generating a hybrid predictive model by establishing an upper threshold and a lower threshold within or at an endpoint of the scale, wherein the hybrid predictive model is configured to, during use [Mental process and Mathematical Algorithm] :
if the probability is below the lower threshold, output as the prediction the first one of the at least two possible bed types [Mental process and Mathematical Algorithm];
if the probability is above the upper threshold, output as the prediction the second one of the at least two possible bed types [Mental process and Mathematical Algorithm];
if the probability is in between the lower threshold and the upper threshold, recommend or refer to an expert selection of the bed type [Mental process and Mathematical Algorithm],
wherein generating the hybrid model comprises selecting the upper threshold and the lower threshold to optimize a performance metric using the postoperative bed type indicated by the medical data as prediction target.
The examiner submits that the foregoing bolded limitation(s) constitute a “Mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, using “medical data comprising records of surgeries …” in the context of this claim encompasses a person (medical professional) looking at data collected and forming a simple judgement as to what type of bed should be assigned to a patient to maximize recovery. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. see MPEP 2106.04(II)(A)(2) and MPEP 2106.04(d)(2). It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception 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.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” [with a description of the additional limitations in brackets], while the bolded portions continue to represent the “abstract idea”.):
1. A system for generating a predictive model for predicting a postoperative bed type for use by a patient after surgery, comprising:
an input interface for accessing medical data comprising records of surgeries, wherein a record of a surgery is indicative of a postoperative bed type used by a patient after the surgery, wherein the postoperative bed type is one of at least two possible bed types, wherein the medical data comprises data characterizing the surgery and the patient [pre-solution activity (data gathering) using generic sensors];
a processor subsystem configured to generate a predictive model for predicting the postoperative bed type to be used by a patient after surgery [applying the abstract idea (mental process or algorithm) using generic computing module] the processor subsystem configured to:
identify, in the medical data, a set of features relevant for prediction of the postoperative bed type in particular field of the surgery [applying the abstract idea (mental process or algorithm) using generic computing module];
training a predictive model on the medical data, wherein the training uses the postoperative bed type as prediction target, wherein the predictive model is configured to output a probability on a scale which corresponds to, at its lower end, a prediction of a first one of the at least two possible bed types and, at its upper end, a prediction of a second one of the at least two possible bed types [Mental process and Mathematical Algorithm];
generating a hybrid predictive model by establishing an upper threshold and a lower threshold within or at an endpoint of the scale, wherein the hybrid predictive model is configured to, during use [Mental process and Mathematical Algorithm] :
if the probability is below the lower threshold, output as the prediction the first one of the at least two possible bed types [Mental process and Mathematical Algorithm];
if the probability is above the upper threshold, output as the prediction the second one of the at least two possible bed types [Mental process and Mathematical Algorithm];
if the probability is in between the lower threshold and the upper threshold, recommend or refer to an expert selection of the bed type [Mental process and Mathematical Algorithm],
wherein generating the hybrid model comprises selecting the upper threshold and the lower threshold to optimize a performance metric using the postoperative bed type indicated by the medical data as prediction target [Post-Solution Activity].
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “accessing medical data comprising records of surgeries …,” “generate a predictive model …,” and “generating the hybrid model comprises selecting the upper threshold and the lower threshold to optimize a performance metric …,” the examiner submits that these limitations are insignificant extra-solution activities that merely use a processor (computer/controller) to perform the process. In particular, the collecting and inputting steps from the medical records and from an input source such as a data storage are recited at a high level of generality (i.e. as a general means of gathering medical and patient condition data for use in the evaluating step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Lastly, the “processor subsystem” is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of ranking information based on a determined amount of use) such that it amounts no more than mere instructions to apply the exception using a generic computer component.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or 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 a whole is not more than a drafting effort designed to monopolize the exception. see MPEP § 2106.05. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor subsystem to perform the training and generation of a predictive model… amounts to nothing more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “accessing medical data comprising records of surgeries …,” “generate a predictive model …,” and “generating the hybrid model comprises selecting the upper threshold and the lower threshold to optimize a performance metric …,” the examiner submits that these limitations are insignificant extra-solution activities. In addition, these additional limitations (and the combination, thereof) amount to no more than what is well-understood, routine and conventional activity. Hence, the claim is not patent eligible.
Claim 2 recites a system including at least one step for defining parameters that the abstract idea needs to optimized and does not limit the judicial exception to a practical application.
Claim 3 recites a system including at least one step for defining parameters by labeling the parameters to the different bed types that the abstract idea needs to optimized and does not limit the judicial exception to a practical application.
Claim 4 recites a system including at least one step to add mathematical constraints (penalty) to the performance metrics so that the abstract idea can optimize and does not limit the judicial exception to a practical application.
Claim 5 recites a system including at least one step to add mathematical constraints (reward) to the performance metrics so that the abstract idea can optimize and does not limit the judicial exception to a practical application.
Claim 6 recites a system including at least one step to evaluate and select the three (3) threshold limits of the abstract idea which do not limit the judicial exception to a practical application.
Claim 7 recites a system including at least one step to use data gathering steps like feature extraction and training using well known mathematical algorithm like gradient boosting that do not limit the judicial exception to a practical application.
Claim 8 recites a system including at least one step perform by the generic processor subsystem to perform pre-processing on received record to enhance the data gathering , evaluate the sufficiency of the records, performing a logical operation on the sufficiency of the records, and the training on the records determined to be sufficient amount to data gathering that do not limit the judicial exception to a practical application.
Claim 9 recites a system including at least one step to use data gathering step like selecting records that meet a certain time constraint that do not limit the judicial exception to a practical application.
Claim 10 recites a system including at least one step for defining parameters that the abstract idea needs to optimized which are further defined to be selectable by an operator and does not limit the judicial exception to a practical application.
Claim 11 recites the same limitations as claim 1, these claims are likewise rejected as being directed to an abstract idea. While each of these limitations, as drafted, are a simple process/acts that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of by “a processor subsystem” and by “an input interface”. That is, other than reciting interface and processor nothing in the claim elements precludes the step from practically being performed in the mind. For example, but for the “a processor subsystem” language, the claim encompasses a person looking at data collected and forming a simple judgement. The mere nominal recitation of by a processor/controller or the like does not take the claim limitations out of the mental process grouping. Thus, the claim recites a mental process.
Claim 12 recites a system including at least one step for defining parameters that the abstract idea needs to optimized which are further defined to be selectable by a clinician and does not limit the judicial exception to a practical application.
Claim 13 recites the same limitations as claim 1 but in method form, this claim is likewise rejected as being directed to an abstract idea as explained above.
Additionally, Claim 15 incorporates the deficiencies outline above with respect to claim 13.
Added claim 16-20 are similar to claims 2-10 and the analysis of these claims is applicable to newly added claims 16-20.
Thus, since independent claims 1, 11, 13, and 15 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that the independent claims are directed towards non-statutory subject matter.
Therefore, the invention of claims 1-4 and 15-20 as a whole, considering all claim elements both individually and in combination, are not patent eligible under 35 USC §101.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Sun; Louise (US-20230146521-A1) HEALTH CARE RESOURCES MANAGEMENT;
Thomas; Bex George et al. (US-20210098090-A1) SYSTEM AND METHOD FOR IDENTIFYING COMPLEX PATIENTS, FORECASTING OUTCOMES AND PLANNING FOR POST DISCHARGE CARE;
Day; Andrew et al. (US-20210193302-A1) OPTIMIZING PATIENT PLACEMENT AND SEQUENCING IN A DYNAMIC MEDICAL SYSTEM USING A COMPLEX HEURISTIC WITH EMBEDDED MACHINE LEARNING;
Nacey; Gene E. (US-8560580-B1) Visual display of room information.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ELLIS B. RAMIREZ whose telephone number is (571)272-8920. The examiner can normally be reached 7:30 am to 5:00pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ramon Mercado can be reached at 571-270-5744. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ELLIS B. RAMIREZ/Examiner, Art Unit 3658