DETAILED ACTION
Acknowledgements
This action is in response to Applicant’s filing on Nov. 18, 2025, and is made Non-Final. This action is being examined by James H. Miller, who is in the eastern time zone (EST), and who can be reached by email at James.Miller1@uspto.gov or by telephone at (469) 295-9082.
Interviews
Examiner interviews are available by telephone or, preferably, by video conferencing using the USPTO’s web-based collaboration platform. Applicants are strongly encouraged to schedule via the USPTO Automated Interview Request (AIR) portal at http://www.uspto.gov/interviewpractice. Each AIR should specifically explain how the interview will advance prosecution—for example, by identifying targeted arguments responsive to the rejection of record, alleged defects in the examiner’s analysis, proposed claim amendments, or another concrete basis for discussion. See MPEP § 713. “Sounding out” the examiner is not permitted. See MPEP § 713.03. The Office is strictly enforcing interview practice.
The examiner is generally available Monday through Friday, 10:00 a.m. to 4:00 p.m. Eastern Time. For any GRANTED Interview Request, the applicant can expect an email within 24 hours confirming an interview slot from the dates/times proposed and providing collaboration tool access instructions. For any DENIED Interview Request, the record will include a communication explaining the reason for denial.
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55, filed Dec. 22, 2023.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 Nov. 18, 2025, has been entered.
Claim Status
The status of claims is as follows:
Claims 1–19 remain pending and examined with Claims 1 and 19 in independent form.
Claims 1, 3, 6, 11, 17, and 19 are presently amended.
No Claims are presently cancelled or added.
Response to Amendment
Applicant's Amendment has been reviewed against Applicant’s Specification filed Aug. 23, 2023, [“Applicant’s Specification”] and accepted for examination.
Applicant's Amendment to address claim objections has been reviewed and has overcome each and every objection to the claims previously set forth in the Final Office Action mailed Aug. 18, 2025 [“Final Office Action"]. The objection to Claims 1–19 is withdrawn.
Response to Arguments
Drawings
Applicant adds new Fig. 10 to address the drawing objections from the Final Office Action, and requests its entry.
For the foregoing reasons, entry is DENIED. Examiner is unable to identify support for all elements and communications paths (i.e., the structure) of new Fig. 10 and the drawing is non-complaint. Specifically, there is a box around elements 10, 11, and 13. It is unclear if the UW system 1 also includes the risk-transfer structure (which is unlabeled) and the circle with elements 331, 121, 122 (which is unlabeled), or the UW system 1 merely incudes the box around elements 10, 11, 13. Element 1 is point to both. Elements 105, 12, 3, 31,332, 34, 341, 342, 343, 34i, 35, 351, 352, 353, and 35i, identified in the specification, ¶¶ 58, 60, 64, 65, 67, 68, 69, 70, and 71, are not identified by the drawings. The flowchart for element 11 is orientated improperly and support cannot be located for the steps. The font for the text is non-complaint. Element labels are missing or not located with the text (e.g., elements 1, 11). There is a cloud showing two-way communication between element 13 and the circle (unlabeled) with people. Keyword “cloud” is not identified in the specification and this cloud feature cannot be located.
Applicant is requested to identify specifically identify where support is located for the amendments to Fig. 10. MPEP § 714.02 (“Applicant should also specifically point out the support for any amendments made to the disclosure.”); 37 CFR § 1.121(d) (“All changes to the drawings shall be explained, in detail, in either the drawing amendment or remarks section of the amendment paper.”). Applicant is further requested to review the drawing for compliance with 37 C.F.R. §§ 1.81, 1.84, 1.85. Examiner is not persuaded the structure and elements in new Fig. 10 are explicitly disclosed by the current, as-filed specification. Accordingly, Fig 10 is denied entry in its entirety. The Drawing Rejection in the Final Office Action is maintained and updated.
35 U.S.C. § 101 Argument
Applicant argues the amended claims are not directed to an abstract idea but rather to a technical solution to the specific problem of point-of sale underwiring with constrained computing resources. Applicant’s Reply at 16–7. Applicant identifies that prior art automated underwriting systems require preliminary data extraction and processing steps (metadata extraction via markup detection, performance measurement parameter extraction) before the machine-learning classifier can operate. This multi-stage process is incompatible with point-of-sale environments where: (1) No human expert is available to manually adapt questions; (2) Computing power is severely limited; and (3) Results must be delivered within minutes. Id. at 17. The claimed invention addresses this by:
Optimized question/rule generation: The system automatically generates an optimized minimal set of linking rules and questions (dynamic decision-tree structure) that requires only the "smallest possible data set" to be captured. Id.
Efficiency gains: By capturing only essential medical parameters and using the optimized decision tree, the system achieves: 90-95% applicant capture rate with a minimal question set; 1000-fold reduction in CPU time (as stated in the specification); and processing within minutes on resource-constrained point-of-sale machines. Id.
Differentiation from prior art: Unlike prior art systems that require sequential preprocessing stages (metadata extraction → machine learning → prediction structure), the claimed system consolidates this into a single, streamlined decision-tree-based process that functions with limited computing resources.
Examiner respectfully disagrees.
Improvements in the functioning of a computer are evaluated using a two-step process. First, “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). “[I]f 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.” Id. Second, “the claim must be evaluated to ensure the claim itself reflects the disclosed improvement in technology.” Id. “An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome.” Id.
Applicant’s Specification teaches the purported technical improvement stems from using “Classification and Regression Trees” (CART) “data mining techniques” to analyze historical data and generate an optimized, minimal question set. Spec. ¶ 48. The specification confirms that the claimed “optimization” is achieved through well-known machine learning and statistical techniques—specifically CART (Classification and Regression Trees)—which are expressly acknowledged as prior art in the specification itself. Spec. ¶ 48 (“the historical medical event dataset can e.g. be assessed using data mining techniques such as Classification and Regression Trees to determine the relevance of each X gathered, as a predictor.”). CART is a well-established statistical method used to build decision trees by recursively partitioning data to identify the most predictive features. Using CART to optimize question selection for classification tasks is a conventional application of this known technique. The specification does not explain any unconventional implementation of CART or identify any technical modification to how the decision tree algorithm functions. CART can further can be performed manually and without the aid of a computer. NPL Leskovec, Jure, Anand Rajaraman, and Jeffrey David Ullman. "Mining of Massive Datasets," Section 12.5 (Decision Trees), Example 12.14 (manual performance) (2019) (cited PTO-892).
The purported “1000x CPU reduction” results from: (1) Asking fewer questions (reducing data input requirements—a business/process improvement, not a technological one); (2) Achieving 90-95% coverage (a coverage/accuracy tradeoff that the specification acknowledges as inherent to all automated decision systems). Applicant’s Specification teaches, “The number of linking rules and/or linking questions of the set can e.g. be adapted and/or reduced and/or increased until a minimal set of linking rules and/or linking questions capture a predefined percentage of processed medical parameter data set.”. Spec. ¶ 43. This describes tuning the accuracy-versus-coverage tradeoff, which the specification itself identifies as a “design trade-off' common to all automated decision structures. Spec. ¶ 5. Therefore, the decision tree methodology is prior art (CART, acknowledged in ¶ 48). The optimization strategy (minimize questions while maintaining target coverage) is a routine tradeoff described in ¶ 5-6 as known in the field. The CPU savings derive from the business decision to ask fewer questions and accept lower coverage of edge cases (5-10% referred to manual review per ¶19). There is no specific technical implementation of how the computer performs these calculations more efficiently is disclosed. The claims merely apply known machine learning techniques (CART) to the field of underwriting to achieve a business objective (faster underwriting with acceptable coverage).
The specification in ¶¶ 19, 46, teach the system uses "approximately 100 to 200 rules, while the more complex prior art systems typically need to rely on 20,000 rules.” Examiner would note that this is evidence the invention achieves efficiency by covering fewer scenarios (fewer rules = less comprehensive coverage), not by performing computations more efficiently. The system explicitly triages out complex cases to manual review. Spec. ¶¶ 39, 46, which is limiting the scope of automation, not improving computer technology.
Drawings
The drawings are objected to under 37 CFR 1.83(a). The drawings must show every feature of the invention specified in the claims. Therefore, the decision-tree-based electronic signal processing engine, as one example, must be shown or the feature(s) canceled from the claim(s). Few, if any, of the claimed features are shown in any drawing. Applicant should review all the claimed features and drawings for compliance. No new matter should be entered.
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description: automated underwriting (UW) system 1, as one example. Examiner is unable to identify any of the multiple reference signs mentioned in specification.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Interpretation
Under the broadest reasonable interpretation, the following claim terms are presumed to have their plain meaning consistent with the specification as it would be interpreted by one of ordinary skill in the art. MPEP § 2111.
risk-transfer structure is an insurance policy because it shifts specific risks from one party to another in exchange for a premium.
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 1–19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
Analysis
Step 1: Claims 1–19 are directed to a statutory category. Claims 1–18 recite a “system” and are therefore, directed to the statutory category of a “machine.” Claim 19 recites a “method” and is therefore, directed to the statutory category of a "process.”
Representative Claim
Claim 1 is representative [“Rep. Claim 1”] of the subject matter under examination and recites, in part, emphasis added by Examiner to identify limitations with normal font indicating the abstract idea exception, bold limitations indicating additional elements. Each limitation is identified by a letter for later use as a shorthand notation in referencing/describing each limitation. Portions of the claim use italics to identify intended use limitations1 and underline, as needed, in further describing the abstract idea exception:
[A] An optimized digital, automated underwriting (UW) system with a decision-tree-based electronic signal processing2 engine, comprising: processing circuitry configured to
[B] implement the decision-tree-based electronic signal processing engine that uses a minimized decision-tree structure to automate the assessment of an applicant's risk shape profile used for an automated risk-transfer underwriting for the coverage of possible damages impacted by the occurrence of one or more medical events to an applicant,
[C] wherein the coverage is provided by applying a risk-transfer structure of the digital automated UW system to the applicant,
[D] wherein user-specific medical parameter data sets are captured and/or measured by associated capturing or measuring devices via data interfaces of the digital automated UW system, and
[E] wherein each captured medical parameter data set is processed by the electronic signal processing3 engine, the electronic signal processing5 engine transmitting an output signal generated upon processing the medical parameter data set by decision-tree-based structure, and
[F] [wherein] … the output signal automatically triggering or blocking an automated application of the risk-transfer structure upon electronic signal transfer to the digital automated UW system,
[G] extract risk shape pattern at least based on occurrence frequency and impact severity measured based on measured occurrences of the medical events of a historical database,
[H] wherein to validate the historical database mirroring real-world within given boundary conditions, the medical event datasets of the historical database are assessed using Classification and Regression Trees as data mining techniques to determine the relevance of each medical event dataset as a predictor[,]
[I] cluster and link together medical events of the historical database having a similar risk shape pattern, wherein similarity of risk shape pattern is detected if the risk shape pattern of said medical events are detected to be within a defined maximal topological distance within a parameter space given by a medical parameter datasets of a medical event,
[J] a cluster of medical events of the historical database having similar risk shape pattern for all medical events of the same cluster comprising related and/or unrelated medical events, wherein unrelated medical events at least comprise medical events with unrelated clinical pictures and/or unrelated medical causes,
[K] provide the linking of medical events of said historical database to a same cluster by a set of linking rules and/or linking questions forming the decision-tree-based data processing structure of the decision-tree-based electronic signal processing engine,
[L] wherein a decision distribution given by outputted decisions is provided by applying the decision-tree-based data processing structure of the decision-tree-based electronic signal processing engine represents the frequency of medical events measured to be within the same cluster of risk shape pattern, by detecting newly occurring medical events not clusterable by the decision-tree-based electronic signal processing engine due to a missing similarity to existing risk shapes,
[M] generate and add additional linking rules and/or linking questions dedicated to capture and cluster the newly occurring medical events to the set of linking rules and/or linking questions, and
[N] dynamically adapt for the realization of the decision-tree data processing structure, the number of linking rules and/or linking questions of the set by reducing and/or increasing the number of linking rules and/or linking questions until a minimal set of linking rules and/or linking questions capture a predefined percentage of processed medical parameter data set with an output signal that automatically triggers the automated application of the risk-transfer structure of the digital automated UW system, wherein the predefined percentage is equal or above 65% of the processed medical parameter data set.
Claims are directed to an abstract idea exception.
Step 2A, Prong One: Rep. Claim 1 recites “An optimized digital, automated underwriting (UW) system” in the preamble, Limitation A, which a fundamental economic principle/practice under the organizing human activity exception because an “underwriting (UW) system” “describes concepts relating to the economy and commerce,” and includes “hedging, insurance, and mitigating risks.” MPEP § 2106.04(a)(2)(II)(A). “Underwriting” is the process of evaluating risk and determining eligibility for commercial products. Limitations B–N are the required steps to perform “underwriting” and therefore, recite the same exception. Id.
Alternatively4, Limitations B–N, as drafted, recite the abstract idea exception of mental processes that under the broadest reasonable interpretation, cover performance in the human mind or with pen and paper, but for the recitation of the generic computer components indicated in bold. MPEP § 2106.04(a)(2)(III).
Claims recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include:
• a claim 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 such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016);
. . .
• a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind, Classen Immunotherapies, Inc. v. Biogen IDEC, 659 F.3d 1057, 1067, 100 USPQ2d 1492, 1500 (Fed. Cir. 2011).
MPEP § 2106.04(a)(2)(III)(A). For example, but for the generic computer components claim language, here, Limitations B–N, recite collecting information (Limitations D, E, G) and analyzing it (Limitations B, C, F, H, I, J, K, L, M, N), where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind. For example, Limitations B and C are mental processes that are practically performed in the human mind or with pen and paper because it requires mere “observation, evaluation, judgment, and/or opinion” to “use a minimized decision-tree structure” and “apply[ ] a risk-transfer structure [for coverage]” (i.e., an insurance policy, as interpreted). NPL Leskovec is prior art and additional evidence of a human’s ability to use or implement a decision-tree structure without the aid of a computer. NPL Leskovec, p. 331 (Example 9.6) (cited herein on PTO-892); see also Section 12.5, Example 12.14. Likewise, Limitation F is also a mental process that is practically performed in the human mind or with pen and paper because it also requires mere “observation, evaluation, judgment, and opinion” to trigger or block an automated application of the risk-transfer structure (insurance policy) for any reason and in any possible way, which encompasses manual methods. Limitation H is a mental process that is practically performed in the human mind or with pen and paper because it also requires mere “observation, evaluation, judgment, and opinion” to assess medical event datasets using Classification and Regression Trees (CART). Serengil, Sefik IIkin. “A Step by Step CART Decision Tree Example.” (2018) [“NPL Step by Step CART”] (cited herein on PTO-892) is prior art and additional evidence of a human’s ability to assess data using Classification and Regression Tree without the aid of a computer. NPL Step by Step CART, pp 2 (“We will mention a step by step CART decision tree example by hand from scratch.”), 6–17 (CART by hand). Limitations I and J are a mental process that are practically performed in the human mind or with pen and paper because it requires mere “observation, evaluation, judgment, and/or opinion” to cluster and link together medial events having a similar risk shape pattern under the conditions specified for maximal topological distance. Further, collecting and comparing known information are steps that can be practically performed in the human mind under Classen. All of the claimed parameters merely require judgment to perform the claimed actions. Limitations K, L, M, and N are mental process that is practically performed in the human mind or with pen and paper because it also requires mere “observation, evaluation, judgment, and opinion” to link medical events to a same cluster in the manner claimed, detecting newly occurring medial events not clusterable in any known way, adding additional linking rules and questions, adapting the number of linking rules and questions until a predefined percentage of data is collected. “The use of a physical aid (e.g., pencil and paper or a slide rule) to help perform a mental step (e.g., a mathematical calculation) does not negate the mental nature of the limitation, but simply accounts for variations in memory capacity from one person to another” or a multi-step mental process. MPEP § 2106.04(a)(2)(III)(B).
If a claim limitation under BRI, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract idea exception. MPEP § 2106.04(a)(2)(III). Accordingly, the pending claims recite the combination of these abstract idea exceptions.
Step 2A, Prong Two: Rep. Claim 1 does not contain additional elements that integrate the abstract idea exception into a practical application because the additional elements are mere instructions to apply the abstract idea exception. MPEP § 2106.05(f). The additional elements are limited to the computer components and indicated in bold, supra. The additional elements are: An optimized digital, automated underwriting (UW) system [computer] with a decision-tree-based electronic signal processing engine [software] comprising: processing circuitry; digital automated UW system [computer]; associated capturing or measuring devices; data interfaces; electronic characterization of signal [use a computer]; historical database.
Regarding the optimized digital, automated underwriting (UW) system [computer] with a decision-tree-based electronic signal processing engine [software] comprising: processing circuitry; digital automated UW system [computer]; associated capturing or measuring devices; data interfaces; electronic characterization of signal [use a computer]; historical database, Applicant’s Specification does not otherwise describe them or describes them using exemplary language as a general-purpose computer, as a part of a general-purpose computer, or as any known and exemplary (generic) computer component known in the prior art. Thus, Applicant takes the position that such hardware/software is so well known to those of ordinary skill in the art that no explanation is needed under 35 U.S.C. § 112(a). Lindemann Maschinenfabrik GMBH v. Am. Hoist & Derrick Co., 730 F.2d 1452, 1463 (Fed. Cir. 1984) (citing In re Meyers, 410 F.2d 420, 424 (CCPA 1969) (“[T]he specification need not disclose what is well known in the art”). E.g., Spec. p. 4 (“any external data source or real-world link, such as a database table or linked measuring or sensory devices, can be used to supply engine parameters, even by adapting them in real-time based on the real-world link.”); p. 8 (“a [generic] computer-implemented processing-efficient process of developing an automatable person-level cost modelling structure”); p. 8 (“a [generic] computer-implemented, deterministic, decision-tree-based process”); p. 12 (“any positive answer to this threefold rule-based triage-process, or indeed any other health question, can automatically trigger reflex rules and/or linking questions contained within process”); p. 18 (“The term "automated underwriting", as used herein, is understood as the process where electronic means, as e.g. [general] computer means”); p. 22 (“The IDC integration can be provided by a communication plugin of the automated UW system 1 allowing a seamless integration of the UW system 1 into any third party web-sides or the like.”); p. 27–8 (In the mostly manual prior art processes, underwriting is a tedious and labor intensive process on behalf of both the applicant and the underwriter. An applicant must fill out a highly personal questionnaire that delves into almost all aspects of their life which can be up to or even over 2500 questions, an imposing amount of paperwork that can turn applicants off pursuing risk-transfer cover. Further in the prior art, in addition to being tedious on behalf of the applicant, the questionnaires typically must be closely examined by a team of skilled underwriters who must follow guidelines mixed with intuition to arrive at a decision, resulting in a process that takes many weeks to complete. The mixture of guidelines and intuition is a known problem in the risk-transfer industry. There is a need to improve the quantitative methods that make up a technical basis of the underwriting process in order to maintain the relevancy of the industry. The inventive automated UW system 1 with the disclosed inventive efficient, automated UW process and automated pricing process based on the linking and clustering of medical events with similar risk shape patterns, does not show these technical problems.”); see also “Response to § 101 Argument” point heading, supra.
Examiner finds the claimed “processing circuitry” is not recited in Applicant’s Specification but a generic computer would contain such processing circuitry. The absence of “processing circuitry” from the specification further supports the generic and known in the prior art nature of the processing circuitry. The generic processing circuitry, here, appears to perform functions that are programmed by software. Spec. pp. 3, 4. This is a computer doing what it is designed to do—performing directions it is given to follow.
Limitation A describes the engine and processing circuitry configured to perform the steps of the claimed invention, which merely invokes computers or other machinery in its ordinary capacity to receive, store, or transmit data. MPEP § 2106.05(f)(2). Limitations B–N describe the engine and processing circuitry, performing the steps of the claimed invention, which represents the abstract idea exception itself. Performing the steps of the abstract idea exception itself simply adds a general-purpose computer after the fact to an abstract idea exception, MPEP § 2106.05(f)(2), or generically recites an effect of the judicial exception. MPEP § 2106.05(f)(3).
Therefore, the claim as a whole, looking at the additional elements individually and in combination, are no more than mere instructions to apply the exception using generic computer components and is not a practical application. MPEP § 2106.05(f). The additional elements do not integrate the abstract idea exception into a practical application because they do not impose any meaningful limits on the abstract idea exception. Accordingly, Rep. Claim 1 is directed to an abstract idea.
Rep. Claim 1 is not substantially different than Independent Claim 19 and includes all the limitations of Rep. Claim 1. Independent Claim 19 contains no additional elements. Therefore, Independent Claim 19 is also directed to the same abstract idea.
The claims do not provide an inventive concept.
Step 2B: Rep. Claim 1 fails Step 2B because the claim as whole, looking at the additional elements individually and in combination, are not sufficient to amount to significantly more than the recited judicial exception. As discussed with respect to Step 2A, Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer and/or generic computer components. MPEP § 2106.05(f). The same analysis applies here in Step 2B. Mere instructions to apply an exception using a generic computer and/or generic computer components cannot provide an inventive concept. MPEP § 2106.05(I).
The additional elements, taken individually and in combination, do not result in the claim, as a whole, amounting to significantly more than the identified judicial exception.
The pending claims in their combination of additional elements is not inventive. First, the claims are directed to an abstract idea. Second, each additional element represents a currently available generic computer technology, used in the way in which it is commonly used (individually generic). Last, Applicant’s Specification discloses that the combination of additional elements is not inventive. Spec., pp. 3, 4, 8, 12, 18, 22, 27, 28 (known and generic (exemplary) computer equipment as explained and cited supra.)
Thus, Examiner finds the additional elements of Rep. Claim 1 are elements that have been recognized as well-understood, routine, and conventional (“WURC”) activity in the particular field of this invention based on Applicant’s own disclosure5. Spec., pp. 3, 4, 8, 12, 18, 22, 27, 28; MPEP § 2106.05(d). Specifically, Applicant’s Specification discloses the recited additional elements (i.e., the optimized digital, automated underwriting (UW) system [computer] with a decision-tree-based electronic signal processing engine [software] comprising: processing circuitry; digital automated UW system [computer]; associated capturing or measuring devices; data interfaces; electronic characterization of signal [use a computer]; historical database) are limited to generic computer components. These elements do no more than “apply” the recited abstract idea(s) on a known computer (e.g., processing engine) and computer-related components (e.g., historical database). NPL Leskovec is prior art and additional evidence of a human’s ability to use or implement a decision-tree structure without the aid of a computer. NPL Leskovec, p. 331 (Example 9.6) (cited herein on PTO-892). NPL Step by Step CART is prior art and additional evidence of a human’s ability to assess data using a Classification and Regression Tree (CART) without the aid of a computer. NPL Step by Step CART, pp 2 (“We will mention a step by step CART decision tree example by hand from scratch.”), 6–17 (CART by hand). See also “Response to § 101 Argument” point heading, supra. The Examiner also finds the functions of receiving, storing, transmitting, displaying, and processing (e.g., performing mathematical operations on) data, described in Limitations A–N are all normal functions of a generic computer.
There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the additional elements in combination adds nothing that is not already present when looking at the elements individually. Their collective functions merely provide conventional computer implementation of the abstract idea at a high level of generality. Thus, Rep. Claim 1 does not provide an inventive concept.
Rep. Claim 1 is not substantially different than Independent Claim 19 and includes all the limitations of Rep. Claim 1. Independent Claim 19 contains no additional elements. Therefore, Independent Claim 19 is also directed to the same abstract idea.
Dependent Claims Not Significantly More
The dependent claims have been given the full two-part analysis including analyzing the additional limitations both individually and in combination. The dependent claim(s) when analyzed both individually and in combination are also held to be patent ineligible under 35 U.S.C. § 101. Dependent claims are dependent on Independent Claims and include all the limitations of the Independent Claims. Therefore, all dependent claims recite the same Abstract Idea. Dependent claims do not contain additional elements that integrate the abstract idea exception into a practical application or recite an inventive concept because the additional elements: (1) are mere instructions to apply the abstract idea exception; and/or (2) further limit the abstract idea exception of the Independent Claims. The abstract idea itself cannot provide the inventive concept or practical application. MPEP §§ 2106.05(I), 2106.04(d)(III).
Dependent Claims 2–18 all recite “wherein” clauses or limitations that further limit the abstract idea of the Independent Claims and contain no additional elements. An inventive concept or practical application cannot be furnished by an abstract idea exception itself. MPEP §§ 2106.05(I), 2106.04(d)(III).
Conclusion
Claims 1–19 are therefore drawn to ineligible subject matter as they are directed to an abstract idea without significantly more. The analysis above applies to all statutory categories of invention. As such, the presentment of Rep. Claim 1 otherwise styled as another statutory category is subject to the same analysis.
Examiner Statement of Prior Art—No Prior Art Rejections
Based on the prior art search results, the prior art of record fails to anticipate or render obvious the claimed subject matter of the instant application. While some individual features of Claims 1–19 may be shown in the prior art of record—no known reference, alone or in combination, would provide the invention of Claims 1–19.
The prior art most closely resembling the applicant’s claimed invention are:
Nayak et al. (U.S. Pat. Pub. No. 2019/0180379) is pertinent because it discloses an automated, real-time mortality classification and signaling system for real-time risk assessment, and adjustment based on an automated selective multi-level triage process.
FOR: Int. Pat. Pub. No. WO 2004/099943 A2 is pertinent because it discloses a system and process for underwriting insurance applications based on the detection and identification of outlier applications.
NPL: Smart Underwriting System: An Intelligent Decision Support System for Insurance Approval & Risk Assessment, 2018 is pertinent because it discloses an improved and optimized way of underwriting process using Artificial Intelligence using data given to the underwriter is in unstructured format.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES H MILLER whose telephone number is (469)295-9082. The examiner can normally be reached M-F: 10- 4 PM (EST).
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/JAMES H MILLER/ Primary Examiner, Art Unit 3694
1 Statements of intended use fail to limit the scope of the claim under BRI. MPEP § 2103(I)(C).
2 Examiner interprets “decision-tree-based electronic signal processing” characterization of “engine” as a mere label that describes the intended functionality of the claimed “engine” and therefore, is not limiting. See, fn.1, supra.
3 Examiner interprets “electronic signal processing” characterization of “engine” as a mere label that describes the intended functionality of the claimed “engine” and therefore, is not limiting. See, fn.2, supra.
4 “It should be noted that these groupings are not mutually exclusive, i.e., some claims recite limitations that fall within more than one grouping or sub-grouping. … Accordingly, examiners should identify at least one abstract idea grouping, but preferably identify all groupings to the extent possible, if a claim limitation(s) is determined to fall within multiple groupings and proceed with the analysis in Step 2A Prong Two.” MPEP § 2106.04(a).
5 See Changes in Examination Procedure Pertaining to Subject Matter Eligibility, Recent Subject Matter Eligibility Decision (Berkheimer v. HP, Inc.), 3-4, https://www.uspto.gov/sites/default/files/documents/memo-berkheimer-20180419.PDF (April, 18, 2018) (That additional elements are well-understood, routine, or conventional may be supported by various forms of evidence, including "[a] citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s).").