The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
The following is in response to the amendments and arguments filed 2/17/2026 and entered with the RCE filed 3/2/2026. Claims 1-12 and 14-21 are pending. Claim 13 has been cancelled.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 2/17/2026 has been entered.
Specification
The abstract of the disclosure is objected to because it is not a concise statement of the technical disclosure of the patent and should include that which is new in the art to which the invention pertains (see below, emphasis added). Correction is required. See MPEP § 608.01(b).
Applicant is reminded of the proper content of an abstract of the disclosure.
A patent abstract is a concise statement of the technical disclosure of the patent and should include that which is new in the art to which the invention pertains. The abstract should not refer to purported merits or speculative applications of the invention and should not compare the invention with the prior art.
If the patent is of a basic nature, the entire technical disclosure may be new in the art, and the abstract should be directed to the entire disclosure. If the patent is in the nature of an improvement in an old apparatus, process, product, or composition, the abstract should include the technical disclosure of the improvement. The abstract should also mention by way of example any preferred modifications or alternatives.
Where applicable, the abstract should include the following: (1) if a machine or apparatus, its organization and operation; (2) if an article, its method of making; (3) if a chemical compound, its identity and use; (4) if a mixture, its ingredients; (5) if a process, the steps.
Extensive mechanical and design details of an apparatus should not be included in the abstract. The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length.
See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Objections
Claims 1, 18 and 19 are objected to because of the following informalities:
Where a claim sets forth a plurality of elements or steps, each element or step of the claim should be separated by a line indentation (see 37 CFR 1.75 (i)).
Appropriate correction is required.
Further, claim 1 recites in the preamble “computer-implemented method” however, there is no computer recited in the body of the claim. The same applies to the dependent claims 2-12, 14-17 and 21.
Claim Rejections - 35 USC § 112
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 1-12 and 14-21 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 "the identifying" in line 14. There is insufficient antecedent basis for this limitation in the claim. The claim includes two different steps of identifying and it is unclear to which identifying the limitation is referring. Claims 18 and 19 recite the same limitation and as such are rejected for similar reasoning.
Dependent claims 2-12, 14-17 and 20-21 inherit the deficiencies of independent claim 1, 18 and 19, respectively, and are therefore also rejected.
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 1-12 and 14-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite an abstract idea. This judicial exception without significantly more. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Claims 1-12 and 14-21 are directed to a method, system and product. The claims fall within one of the four statutory categories of invention, processes, machines, manufactures and compositions of matter.
The Examiner has identified independent method Claim 1 as the claim that represents the claimed invention for analysis and is similar to independent product Claim 18 and system Claim 19.
The claims recite the steps of identifying a plurality of key features that contribute to a level of anomalousness of an anomalous subgroup;
identifying one or more minimal perturbations to a set of features of the anomalous subgroup that result in a reduction of the level of anomalousness;
wherein the identifying the one or more minimal perturbations comprises forming and evaluating a resultant subgroup by modifying a search tree based on a set of features of a complement subgroup, traversing the resultant subgroup when evaluation of the resultant subgroup satisfies a predetermined anomalousness criteria, and backtracking the traversal when evaluation of the resultant subgroup fails to satisfy the predetermined anomalousness criteria,
wherein the predetermined anomalousness criteria correspond to the reduction of the level of anomalousness, and
wherein the identifying further comprises iteratively substituting and evaluating the set of features of the complement subgroup until a space of substitutions is exhausted; and
applying the one or more minimal perturbations to members of the anomalous subgroup.
Under Step 2A Prong 1, the claim as a whole recites the series of steps instructing how to analyze data for anomalousness (analysis of differentiated subgroups) which falls within the abstract grouping of Mental Processes. In evaluating whether a claim that requires a computer recites a mental process, the broadest reasonable interpretation of the claim in light of the specification is considered. The claimed invention is described as a concept that is performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer, 2) in a computer environment, and 3) is merely using a computer as a tool to perform the concept. The claim is considered to recite a mental process. Thus, the claim recites an abstract idea.
Under Step 2A prong 2, this judicial exception is not integrated into a practical application. The claim as a whole merely describes how to generally “apply” the concept of how to analyze data for anomalousness (analysis of differentiated subgroups) in a computer environment. The claimed computer components (in claims 18 of a tangible computer-readable storage media and in claim 19 of a memory and processor) are recited at a high level of generality and are merely being used as tools to perform the data analysis method. Simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea. Accordingly, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
Under Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A prong 2, the claim describes how to generally “apply” the concept of analyzing data for anomalousness (analysis of differentiated subgroups) in a computer environment and merely being used as tools to perform the concept. Thus, even when viewed separately and as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. The claim is ineligible.
The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it".
Dependent claims, 2-12, 14-17 and 20-21, further define the abstract idea that is present in their respective independent claims 1, 18, and 19 (ranking data, identifying, calculating data, evaluating data, altering features). The dependent claims are abstract for the reasons presented above because there are no additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered as a whole, individually and as an ordered combination. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words "apply it". Thus, the claims 1-12, 14-21 are not patent-eligible.
Also, the dependent claims further limit the abstract idea to a more narrow abstract idea by further including steps which fall within the mental processes and/or mathematical concepts subgroupings of abstract ideas such as: ranking the key features (claim 2), computing a standard deviation (claim 3), calculating deviations (claim 4), scoring a contribution of a selected feature (claim 5), use cross-substitution by minimally altering a version of a defining set of features of the anomalous subgroup…which starts with a highest ranked feature of the identified key features to create a new subgroup (claims 6 and 7), statistically evaluating the scores of the version of the defining set of features to identify a set of perturbations to the set of features of the anomalous subgroup that bring the anomalous distribution to a normal distribution (claim 8), halting the method when a statistical significance of the minimally altered version of the defining set of features surpasses a given threshold (claim 9), obtaining measures of effect, the measures of effect including an odds ratio and a p-value, that define the statistical significance and determining a threshold measure to identify when a corresponding score has significantly dropped (claim 10), computing one or more characterization metrics as scores to describe the level of anomalousness, odds ratios between the anomalous subgroup and an overall population where the odds ratios evaluate a likelihood of experiencing an outcome of an interest in each subset resulting from substitutions compared to the overall population, a confidence interval, and an empirical p-value of the odds ratios defined by the formula provided (claim 11), a further set of steps for identifying the one or more minimal perturbations (claim 12), deriving a scoring metric from an expectation- based scan statistic similar to a metric employed in a corresponding discovery method (claim 14), cross-substitution function is optimized to run in optimal time (claim 15), computing a weighted contribution of a given feature and corresponding feature value to the level of anomalousness by scoring a deviation of each unique value of the given feature for the anomalous subgroup in comparison to the entire population (claim 16), generating … a set of prescribed medical therapies based on the one or more minimal perturbations (claim 17), calculating a feature relevance in response to the facilitating the application, … determining a corresponding distribution, calculating deviations of feature values, and ranking the feature values based on relevance, performing cross-substitution, and returning a set of substitutions (claim 21). Such narrowing creates a more narrow abstract idea but does not transform the abstract idea into patent-eligible subject matter. The “administering” in claim 17 is considered a field-of-use limitation (see Mayo 566 U.S. at 76, 101 USPQ2d at 1967).
Applicant’s claims are not patent-eligible.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 2, 5-12, 14-16 and 21 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Mulang et al. (2021, “Post-discovery analysis of anomalous subsets” 35th Conference on Neural Information Processing systems (NeurIPS 2021) Sydney Australia, pp 1-9).
Regarding claim 1, Mulang et al. disclose a method comprising: identifying a plurality of key features that contribute to a level of anomalousness of an anomalous subgroup (takes as an anomalous subset and identifies the most significant features and feature values contributing to anomalousness – pg. 3 “Methods” first paragraph; identifying the features and feature values that are most relevant to the anomalousness of a subset – pg. 5 “3.4 Cross Substitution” first paragraph);
identifying one or more minimal perturbations to a set of features of the anomalous subgroup that result in a reduction of the level of anomalousness (find minimal changes in the anomalous subset that results in a significant drop in the anomalous score – pg. 5 “3.4 Cross Substitution” first paragraph; Statistical significance test is used to determine whether the new subset loses the anomalousness - pg. 5 “3.4 Cross Substitution” second paragraph; see figure 1);
wherein the identifying the one or more minimal perturbations comprises forming and evaluating a resultant subgroup by modifying a search tree based on a set of features of a complement subgroup, traversing the resultant subgroup when evaluation of the resultant subgroup satisfies a predetermined anomalousness criteria, and backtracking the traversal when evaluation of the resultant subgroup fails to satisfy the predetermined anomalousness criteria (See method section 3, pages 3-5, specifically, sections 3.1-3.4, find minimal changes in the anomalous subset that results in a significant drop in the anomalous score – pg. 5 “3.4 Cross Substitution” first paragraph; Statistical significance test is used to determine whether the new subset loses the anomalousness - pg. 5 “3.4 Cross Substitution” second paragraph; see figure 1), wherein the predetermined anomalousness criteria correspond to the reduction of the level of anomalousness, and wherein the identifying further comprises iteratively substituting and evaluating the set of features of the complement subgroup until a space of substitutions is exhausted (see figure 1, section 3.3 and 3.4) ; and applying the one or more minimal perturbations to members of the anomalous subgroup (this work lays the foundation for the discussion concerning the design of interventions…inspire better design of interventions – pg. 8 “Conclusion”)
Regarding claim 2, ranking the identified key features (rank the feature values – pg. 4 “3.3 Quantifying Feature Relevance to Anomalousness of a Subset” last sentence of paragraph; formula for ranking at top of pg. 5).
Regarding claim 5, the identifying the plurality of key features further comprises scoring a contribution of a selected feature of the plurality of key features to the level of anomalousness of the anomalous subgroup (pg. 4 “3.3 Quantifying Feature Relevance to Anomalousness of a Subset”).
Regarding claim 6, the identifying the one or more minimal perturbations uses cross-substitution by minimally altering a version of a defining set of features of the anomalous subgroup obtained by replacing a value of the version of the defining set of features with a value from a complement set of features of a complement subgroup and scoring the version of the defining set of features during a cross-substitution phase (cross-substitution, perturbations, scoring function - pg. 5 “3.4 Cross Substitution”).
Regarding claim 7, the minimally altering of the version of the defining set of features starts with a highest ranked feature of the identified key features to create a new subgroup (being alteration in order of the feature ranking; substitution results in a new subset - pg. 5 “3.4 Cross Substitution”).
Regarding claim 8, statistically evaluating the scores of the version of the defining set of features to identify a set of perturbations to the set of features of the anomalous subgroup that bring the anomalous distribution to a normal distribution (statistical significance test scoring determines whether the new subset loses the anomalousness - pg. 5 “3.4 Cross Substitution” (if subsets are calculating as losing the anomalousness then by virtue they are being brought to a normal distribution)).
Regarding claim 9, halting the method when a statistical significance of the minimally altered version of the defining set of features surpasses a given threshold (stopping criterion threshold - pg. 5 “3.4 Cross Substitution”).
Regarding claim 10, obtaining measures of effect, the measures of effect including an odds ratio and a p-value, that define the statistical significance and determining a threshold measure to identify when a corresponding score has significantly dropped wherein the odds ratio is defined by 07, = tn git rg and is a vector of length equal to a number of unique values per feature where 0,7, is the odds ratio of a uv" value of an m" feature, u%, is a mean score of all records with the p™ value of the mth feature, and fg is a global mean of all records. (statistical significance, odds ratio, p-value and threshold– pg. 5 “3.4 Cross Substitution”).
Regarding claim 11, further comprising computing one or more characterization metrics as scores to describe the level of anomalousness, odds ratios between the anomalous subgroup and an overall population where the odds ratios evaluate a likelihood of experiencing an outcome of an interest in each subset resulting from substitutions compared to the overall population, a confidence interval, and an empirical p-value of the odds ratios defined by (scoring, odds ratio, p-value and formula – pg. 5 “3.4 Cross Substitution” and Algorithm 1):
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where
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(pg. 4 mean formula) D represents the overall population, and Xnorm is a set of features and corresponding feature values obtained from a given combination of perturbations of the set of features of the anomalous subgroup with incremental perturbations, q is an assumed constant multiplicative increase in outcome odds for any given subgroup (variables – pgs. 3-4 “Problem Formulation”).
Regarding claim 12, identifying the one or more minimal perturbations further comprises: clearing a set of substitutions; determining a lower confidence interval of the anomalous subgroup and the newly created subset resulting from the perturbation; returning an indication of an empty set in response to the subgroup being equivalent to the domain; returning the set of substitutions in response to the lower confidence interval of the anomalous subgroup being less than an upper confidence interval of the domain or all substitutions having been considered; adding a current substitution to the set of substitutions in response to a lower confidence interval of a current subgroup is less than the lower confidence interval of the anomalous subset; setting a value of the current subgroup to a difference between the upper confidence interval of the domain and the lower confidence interval of a current subset if the lower confidence interval of the current subgroup is less than the lower confidence interval of the anomalous subgroup; selecting a next substitution; generating a new subgroup based on the current subset and the selected next substitution; generating a statistical measure of the lower confidence interval of the current subgroup and an upper confidence interval of the current subgroup; iteratively calling the method with a new lower confidence interval and the new subgroup; and providing the set of substitutions (pg. 5 “3.4 Cross Substitution”; confidence interval – pg. 6 “4.2”).
Regarding claim 14, deriving a scoring metric from an expectation- based scan statistic similar to a metric employed in a corresponding discovery method (scoring – pg. 5 “3.4 Cross Substitution”).
Regarding claim 15, wherein a cross-substitution function is optimized to run in optimal time (by setting a threshold this is considered optimizing – pg. 5 “3.4 Cross Substitution”).
Regarding claim 16, computing a weighted contribution of a given feature and corresponding feature value to the level of anomalousness by scoring a deviation of each unique value of the given feature for the anomalous subgroup in comparison to the entire population (pg. 4 “3.3 Quantifying Feature Relevance to Anomalousness of a Subset”).
Regarding claim 21, calculating a feature relevance in response to the facilitating the application, wherein the calculating the feature relevance further comprises determining a corresponding distribution, calculating deviations of feature values, and ranking the feature values based on relevance; performing cross-substitution; and returning a set of substitutions (statistical significance, odds ratio, p-value and threshold– pg. 5 “3.4 Cross Substitution”).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 3-4 are rejected under 35 U.S.C. 103 as being unpatentable over Mulang, et al., as applied in claims 1 and 2 above, further in view of Thomas (“ A Step-by-Step Guide on How to Calculate Standard Deviation”. Outlier October 6, 2021. https://articles.outlier.org/a-step-by-step-guide-on-how-to-calculate-standard-deviation. (hereinafter “Thomas”).
Regarding claim 3, Mulang discloses the method of claim 2 as shown above and further discloses wherein the ranking the identified key features further comprises:
(see Thomas below for teaching “computing a standard deviation σց of a given feature value”) where a global mean µց is an overall mean of outputs in an original dataset D defined as: (see the formula for mean on pg. 4 in “3.3 Quantifying Feature Relevance to Anomalousness of a Subset”);
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(see Thomas below for teaching “computing a subset mean µss, defined as a mean of all outputs of records containing feature values from the set of features of the anomalous subgroup”);
for each feature value fv in the set of features of the anomalous subgroup, adding a given record in the original dataset D to a set of records-fv if the given record has the feature value fv, and obtaining, for every ith record in the set of records-fv, a marginal output for the given feature value for an ith record where ai equals a y value of the ith record in the set of records having the feature value (pg. 4 “3.3 Quantifying Feature Relevance to Anomalousness of a Subset”; pg. 5 “3.4 Cross Substitution” paragraphs and tables); and
(see Thomas below for teaching “obtaining a score for each feature value pair of the plurality of key features that contribute to the level of anomalousness by computing a standard deviation from the mean”):
σց =
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but does not specifically disclose computing the subset mean and standard deviation recited in claim 3.
However, Thomas teaches calculating the mean of your data (see Step 1) and the standard deviation (see Steps 2-5 under “Steps for Calculating Standard Deviation”).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains to modify the calculations taught by Mulang to further include calculations of mean and standard deviation as taught by Thomas in order to gain further insight into the values being analyzed.
Regarding claim 4, calculating, for each feature value fv of the plurality of key features that contribute to the level of anomalousness, deviations of ej from the global mean µց based on 8j = ej - µց, where: (Mulang et al. p4, deviations of ej from the mean expected value of the dataset - see the same formulas on pg. 4 in “3.3 Quantifying Feature Relevance to Anomalousness of a Subset”)
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and wherein fja represents the jth feature of the anomalous subset, E( ) is a function for determining an expected value, and the feature value fv of the plurality of key features that contribute to the level of anomalousness are ranked based on the calculated deviations as: (see same formula top of pg. 5 Mulang et al.)
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Claim(s) 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mulang et al. as applied to claim 1 above, and further in view of in view of Zonca et al (US 2022/0343121 A1).
Regarding claim 17, Mulang et al. disclose the method of claim 1 as reasoned above but does not specifically disclose generating and administering a set of prescribed medical therapies based on the one or more minimal perturbations.
However, in analogous art of application of local interpretable model-agnostic explanations on decision services, Zonca et al teach giving treatments to patients based on the explanatory data generated after multiple perturbations of input data where the explanatory data, which is similar to the most significant features identified in Mulang et al., represent features for why a particular output was determined (see Zonca et al. para 0016-0018, 0020).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains to modify the post-discovery analysis of anomalous subsets taught by Mulang et al., which results in explanatory data of features most relevant to determined anomalous output, to further include using such explanatory data for purposes of giving treatments to patients as taught by Zonca et al. because the explanatory data can make the underlying artificial intelligence employed (AI/ML used in both Zonca et al. and Mulang et al.) more understandable and trustworthy to users (Zonca et al. para [0011]) and therefore patients and doctors can have more confidence in the treatments based on the explanatory data produced.
Regarding claim 18, Mulang et al. disclose the method of claim 1 as reasoned above but does not specifically disclose a computer program product, comprising: one or more tangible computer-readable storage media and program instructions stored on at least one of the one or more tangible computer-readable storage media, the program instructions executable by a processor, the program instructions comprising. However, in analogous art of application of local interpretable model-agnostic explanations on decision services, Zonca teaches an embodiment of a storage device, computer-readable storage medium and processor (0033-0038). It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains to modify the post-discovery analysis of anomalous subsets taught by Mulang to be embodied as a computer program product as taught by Zonca because Zonca teaches similar methods can be effectively embodied as such.
Regarding claim 19, Mulang et al. disclose the method of claim 1 as shown above but does not specifically disclose a system comprising: a memory; and at least one processor, coupled to said memory.
However, in analogous art of application of local interpretable model-agnostic explanations on decision services, Zonca et al. teach an embodiment of an apparatus comprising memory and a processor (Zonca et al. para 0033-0036, 0040).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains to modify the post-discovery analysis of anomalous subsets taught by Mulang to be embodied as an apparatus as taught by Zonca because Zonca teaches similar methods can be effectively embodied as such.
Regarding claim 20, the operations further comprising ranking the identified key features (see Mulang et al. rank the feature values – pg. 4 “3.3 Quantifying Feature Relevance to Anomalousness of a Subset” last sentence of paragraph; formula for ranking at top of pg. 5).
Response to Arguments
Applicant's arguments filed 2/17/2026, entered 2/26/26, have been fully considered but they are not persuasive.
35 USC 101 Subject Matter Eligibility
Step 2A prong 1
With regards to applicant’s argument independent claim 1 is not “directed to a mental process, but instead to a specific post discovery analysis framework that performs repeated feature value perturbations that contribute to improvement in computational data analysis” (see rem 11), Examiner respectfully disagrees.
In Step 2A prong 1, the inquiry determines whether a claim recites a judicial exception, Applicant’s argument is directed to prong 2, practical application. The claims recite the abstract idea of Mental processes as reasoned in the above rejection. Further, claims can recite a mental process even if they are claimed as being performed on a computer. 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. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer"). See MPEP 2106.04. Versata, in which the patentee claimed a system and method for determining a price of a product offered to a purchasing organization that was implemented using general purpose computer hardware. 793 F.3d at 1312-13, 1331, 115 USPQ2d at 1685, 1699. The Federal Circuit acknowledged that the claims were performed on a generic computer, but still described the claims as "directed to the abstract idea of determining a price, using organizational and product group hierarchies, in the same way that the claims in Alice were directed to the abstract idea of intermediated settlement, and the claims in Bilski were directed to the abstract idea of risk hedging." 793 F.3d at 1333; 115 USPQ2d at 1700-01. See MPEP 2106.04.
Applicant further argues the specification discloses a technical problem of identifying anomalous subgroups and characterizing the subgroups (see rem 11). Examiner respectfully disagrees. The specification provides for an analysis, math or computational mental processing, problem with a technical solution and not a technical problem.
For the purpose of responding to applicants argument and the spirit of compact prosecution, the arguments directed to 2A step 1 (rem 11-13) will be considered for Step 2A prong 2.
Regarding applicant’s arguments with respect to Ex Parte Desjardins (rem 12-13), examiner respectfully disagrees.
See Revised MPEP 2106.04(d)(1), if the specification explicitly sets forth an improvement but only 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 that the claim improves technology or a technical field. Second, if the specification sets forth an improvement in technology or a technical field, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement, i.e., that is, the claim includes the components or steps of the invention that provide the improvement described in the specification. "
Further, MPEP 2106(f), REVISED, states “in Ex Parte Desjardins, the claims reflected a specific improvement that addressed the technical problem of “catastrophic forgetting” in continual learning systems, while allowing artificial intelligence systems to variously optimize system performance, use less storage capacity and reduce system complexity. Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision) (precedential). "
Desjardins is not relevant in this application. This is all something someone could do mentally. In the specification, a brief/broad improvement is provided (Specifically as to claim pages 3-4). The specification is silent to an improvement in the technology nor AI/ML functioning. It is improving the data, not the technology. In addition, the claim limitations do not recite the AI or machine learning. The claims have limitations to search trees (those can be used in AI, but not inherently AI).
Thus, because the Specification describes the additional elements in general terms, without describing the particulars, the claim limitations may be broadly but reasonably construed as reciting conventional computer components and techniques, particularly in light of the Specification.
To show that the involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology. See MPEP § 2106.05(f) for more information about mere instructions to apply an exception.
Attorney arguments cannot take the place of evidence in the record. Must provide facts to back up your position.
Regarding applicant’s argument Mulang et al. does not disclose “Mulang fails to disclose any backtracking algorithm for identifying the minimal perturbations to a set of features of an anomalous subgroup that result in a reduction of the level of anomalousness, as recited in amended independent claim 1. In fact, Mulang is silent regarding "evaluating a resultant subgroup by modifying a search tree based on a set of features of a complement subgroup, traversing the resultant subgroup when evaluation of the resultant subgroup satisfies a predetermined anomalousness criteria,” Examiner respectfully disagrees (see rem page 16). The recitation “by modifying a search tree based on a set of features of a complement subgroup,” as written, is not positively claimed. Further, the wherein clauses added to the second limitation of claim 1 appear to be disjointed from the invention as described in the originally filed specification. It appears to be combining parts of 2 different embodiments disclosed. Applicant should clarify to provide for the metes and bounds of the claimed invention.
With regards to applicant’s argument with respect to “traversing the resultant subgroup when evaluation of the resultant subgroup satisfies a predetermined anomalousness criteria, and backtracking the traversal when evaluation of the resultant subgroup fails to satisfy the predetermined anomalousness criteria” Examiner respectfully disagrees. In method claims, only those steps that must be performed are considered in the broadest reasonable interpretation (BRI), so the BRI would not include steps contingent on meeting a certain condition.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Huang et al. Anomaly detection in clinical processes. AMIA Annu Symp Proc. 2012;2012. Epub 2012 Nov 3. p370-379
Fisk et al. discloses determining whether new subgraphs that are observed locally in dynamic graphs are indicative of anomalous behavior.
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Kelly S. Campen
Primary Examiner
Art Unit 3691
/KELLY S. CAMPEN/ Primary Examiner, Art Unit 3691