DETAILED ACTION
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 09/04/2026 has been entered.
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 Amendment
In light of the amendments, the previous 112(b) rejections have been withdrawn.
In light of the amendments, the claims are rejected under 35 U.S.C. 101.
Notice to Applicant
In the amendment dated 09/04/2026, the following has occurred: claims 38-39, 43, 46-48, 50-53, and 55-57 have been amended; claims 39-42, 45, 47, and 49 remain unchanged; and no new claims have been added.
Claims 38-57 are pending.
Effective Filing Date: 06/03/2024
Response to Arguments
35 U.S.C. 112(b) Rejections:
Applicant has overcome the 112(b) issues via amendments, Examiner withdraws these rejections.
35 U.S.C. 101 Rejections:
Applicant argues that the claims are directed to a practical application. Applicant points to Step 2A, Prong Two and states that the present claims provide more accurate data and points to the specification. Applicant further states that there is reduction in computing resource usage based on this higher accuracy data. Examiner agrees to a degree. Examiner agrees that there can be a reduction of computing processing, but this is due to an improvement to the data (being more accurate data). Using a computer less because the data is more accurate is not necessarily a technical improvement, though it can be seen as an improvement. This improvement is to the abstract idea itself however involving organizing and creating data.
Additionally, Applicant points to McRO and states that the present claims are similar in that they also do not merely recite a desired result, they recite a specific way of achieving that result. Examiner however respectfully disagrees. McRO involves producing lip synchronization and recites the specific way of achieving that result, whereas the present claims recite the outputting of better data and a specific way to achieve that. The improvement to lip synchronization was over a manual 3-D lip synchronization process. The claims of McRO achieved the following: 1) being specific, rule-based methods for automatically synchronizing lips, 2) these methods improve an existing technological process involving manual 3-D animation using unconventional rules, 3) claims were limited to a particular configuration, and 4) the claims recited a technological improvement rather than a mere abstract idea. Due to the above determination, the claims of McRO did not go past Step 1. The present claims however do go past step 1 as they recite a judicial exception without significantly more. The improvement here appears to be in the data.
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 38-57 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 38-51 are drawn to a system, claims 52-56 are drawn to a method, and claim 57 is drawn to a media, each of which is within the four statutory categories. Claims 38-57 are further directed to an abstract idea on the grounds set out in detail below. As discussed below, the claims do not include additional elements that are sufficient to amount to significantly more than the abstract idea because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea (Step 1: YES).
Step 2A:
Prong One:
Claim 38 recites a system for maintaining data integrity in a computerized health analysis platform, the system comprising:
a) at least one processor; and
b) a memory subsystem communicatively coupled to the at least one processor, the memory subsystem storing instructions which, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
1) accessing one or more first data structures comprising:
a plurality of historical data sets regarding a plurality of entities, wherein each of the historical data sets represents measurements of one or more physiological parameters of the plurality of entities, and
one or more health-related attributes of the plurality of entities;
2) reading, from a data store, c) executable measurement unit determination software comprising d) a data filtration tool and e) a unit determination tool;
3) executing, by the at least one processor, the measurement unit determination software to perform operations comprising:
3a) determining, by the data filtration tool of the executable measurement unit determination software, a first subset of the historical data sets based on the one or more health-related attributes of the plurality of entities; and
3b) based on one or more measurements of the one or more health-related attributes, generating, by the data filtration tool of the executable measurement unit determination software in one or more measurement units, a reference measurement range of the one or more physiological parameters represented in the first subset determining based on the one or more health-related attributes;
4) accessing lab test data regarding one or more target entities, wherein the lab test data represents one or more measurements of the one or more physiological parameters of the one or more target entities, wherein the one or more target entities exhibit the one or more health-related attributes, and wherein the one or more measurements of the lab test data lack a first measurement unit or exhibit a mislabeling error regarding the first measurement unit;
5) based on execution of the measurement unit determination software, determining, by the unit determination tool of the measurement unit determination software and based on the reference measurement range, a second measurement unit for the one or more measurements of the lab data that lack the first measurement unit or exhibit the mislabeling error regarding the first measurement unit;
6) generating, by the at least one processor, a second data structure representing the one or more measurements of the lab test data in association with the second measurement unit;
7) storing, by at the least one processor in f) a hardware storage device, the second data structure representing the one or more measurements of the lab test data in association with the second measurement unit; whereby data quality of the lab test data is improved by associating the second measurement unit with the lab data missing the first measurement unit or exhibiting the labeling error with the first measurement unit; and
8) outputting, by an input/output (I/O) interface to an I/O device, a graphical user interface of the second data structure in a display format.
Claim 38, in part, performing the steps of 1) accessing one or more first data structures comprising: a plurality of historical data sets regarding a plurality of entities, wherein each of the historical data sets represents measurements of one or more physiological parameters of the plurality of entities, and one or more health-related attributes of the plurality of entities, 3) perform operations comprising: 3a) determining, by the data filtration tool (when not software), a first subset of the historical data sets based on the one or more health-related attributes of the plurality of entities and 3b) based on one or more measurements of the one or more health-related attributes, generating, by the data filtration tool in one or more measurement units, a reference measurement range of the one or more physiological parameters represented in the first subset determining based on the one or more health-related attributes, 4) accessing lab test data regarding one or more target entities, wherein the lab test data represents one or more measurements of the one or more physiological parameters of the one or more target entities, wherein the one or more target entities exhibit the one or more health-related attributes, and wherein the one or more measurements of the lab test data lack a first measurement unit or exhibit a mislabeling error regarding the first measurement unit, 5) determining, by the unit determination tool and based on the reference measurement range, a second measurement unit for the one or more measurements of the lab data that lack the first measurement unit or exhibit the mislabeling error regarding the first measurement unit, 6) generating a second data structure representing the one or more measurements of the lab test data in association with the second measurement unit, and 7) storing the second data structure representing the one or more measurements of the lab test data in association with the second measurement unit, whereby data quality of the lab test data is improved by associating the second measurement unit with the lab data missing the first measurement unit or exhibiting the labeling error with the first measurement unit. These steps correspond to Certain Methods of Organizing Human Activity, more particularly, managing personal behavior or relationships or interactions between people (including following rules or instructions). For example, the claim describes how one could organize and create data in the manner above. Independent claims 52 and 57 recite similar limitations and are also directed to an abstract idea under the same analysis.
Depending claims 39-51 and 53-56 include all of the limitations of claims 38 and 52, and therefore likewise incorporate the above described abstract idea. Depending claim 39 adds the additional step of “providing the second data structure to the computerized health analysis platform”; claim 42 adds the additional steps of “comparing measurement values of the one or more physiological parameters of the first subset of the first data sets with each other” and “converting different measurement units of the one or more physiological parameters of the first subset to the one or more measurement units”; claims 43 and 53 add the additional steps of “comparing one or more values of the one or more measurements to the reference measurement range” and “determining, based on the comparison, that the one or more measurements exhibit the mislabeling error or lack the measurement unit”; claims 44 and 54 add the additional steps of “determining a frequency of the one or more values of the one or more measurements that fall within the reference measurement range” and “determining the mislabeling error based on the frequency”; claims 45 and 55 add the additional step of “generating a score based on the comparison of the one or more values of the one or more measurements to the reference measurement range”; claim 46 adds the additional step of “based on comparing the score to a threshold score, determining the one or more measurements exhibit the mislabeling error”; claim 47 adds the additional step of “outputting the second measurement unit to a display of a user interface”; claims 48 and 56 add the additional step of “generating, on the display of the user interface, an indication of whether one or more measurements exhibit the mislabeling error or lack the first measurement unit”; claim 49 adds the additional step of “generating a frequency graph that represents a relationship between a frequency of the one or more measurements and a plurality of measurement units”; claim 50 adds the additional step of “utilizing a machine learning classifier to determine the second measurement unit, wherein the machine learning classifier is trained based on z-score probability and one or more of frequency features, wherein the frequency features comprise a unit frequency by study, a unit frequency by site, and a unit frequency by subject, and wherein utilizing a machine learning classifier to determine the second measurement unit comprises utilizing logistic regression model to predict, based on the z-score probability derived from the reference measurement range and the frequency features, a binary outcome that indicates a possibility of the one or more measurements being measured in one or more respective second measurement units”; and claim 51 adds the additional step of “modifying, based on the second data structure, the lab test data, wherein modifying the lab test data improves data integrity by preventing processing of incomplete or erroneous lab test data, and wherein the second measurement unit (i) is incorporated into the one or more measurements that lack the first measurement unit or (ii) replaces the first measurement unit of the one or more measurements that exhibit the mislabeling error”. Additionally, the limitations of depending claims 40-41 further specify elements from the claims from which they depend on without adding any additional steps. Claims 47-48, 52, and 56 add additional elements to the claims and are addressed below in Prong Two. These additional limitations only further serve to limit the abstract idea. Thus, depending claims 39-51 and 53-56 are nonetheless directed towards fundamentally the same abstract idea as independent claims 38 and 52 (Step 2A (Prong One): YES).
Prong Two:
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of – using a) at least one processor, b) a memory subsystem communicatively coupled to the at least one processor, the memory subsystem storing instructions which, when executed by the at least one processor, cause the at least one processor to perform operations, c) executable measurement unit determination software comprising d) a data filtration tool and e) a unit determination tool, f) a hardware storage device, g) an electronic device (from claims 52 and 56), and h) a user interface (from claims 47, 48, and 56) to perform the claimed steps.
The claims also include the additional element steps of 2) “reading, from a data store, executable measurement unit determination software comprising a data filtration tool and a unit determination tool”, 3) “executing, by the at least one processor, the measurement unit determination software”, and 8) “outputting, by an input/output (I/O) interface to an I/O device, a graphical user interface of the second data structure in a display format”.
The a) at least one processor, b) memory subsystem, c) executable measurement unit determination software comprising d) a data filtration tool and e) a unit determination tool, f) a hardware storage device, g) an electronic device, and h) a user interface in these steps and the additional element steps of 2) “reading, from a data store, executable measurement unit determination software comprising a data filtration tool and a unit determination tool” and 3) “executing, by the at least one processor, the measurement unit determination software” are recited at a high-level of generality (i.e., as generic components performing generic computer functions) such that they amount to no more than mere instructions to apply the exception using generic computer components (see: Applicant’s specification, paragraphs [0083] and [0098] where these components are recited as being generic, see MPEP 2106.05(f)).
Additionally, the additional element step of 8) “outputting, by an input/output (I/O) interface to an I/O device, a graphical user interface of the second data structure in a display format” adds insignificant extra-solution activity to the abstract idea which amounts to insignificant application, see MPEP 2106.05(g).
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea (Step 2A (Prong Two): NO).
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using a) at least one processor, b) a memory subsystem communicatively coupled to the at least one processor, the memory subsystem storing instructions which, when executed by the at least one processor, cause the at least one processor to perform operations, c) executable measurement unit determination software comprising d) a data filtration tool and e) a unit determination tool, f) a hardware storage device, g) an electronic device, and h) a user interface to perform the claimed steps and the additional element steps of 2) “reading, from a data store, executable measurement unit determination software comprising a data filtration tool and a unit determination tool”, 3) “executing, by the at least one processor, the measurement unit determination software”, and 8) “outputting, by an input/output (I/O) interface to an I/O device, a graphical user interface of the second data structure in a display format” amount to no more than insignificant extra-solution activity in the form of mere instructions to apply the exception using generic computer components that does not offer “significantly more” than the abstract idea itself because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of any computer itself, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment. It should be noted that the claims do not include additional elements that amount to significantly more than the judicial exception because the Specification recites mere generic computer components, as discussed above that are being used to apply certain method steps of organizing human activity. Specifically, MPEP 2106.05(d) and MPEP 2106.05(f) recites that the following limitations are not significantly more:
Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)); and
Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)).
The current invention generates and stores a data structure utilizing a) at least one processor, b) a memory subsystem, c) executable measurement unit determination software comprising d) a data filtration tool and e) a unit determination tool, f) a hardware storage device, g) an electronic device, and h) a user interface and the additional element steps of 2) “reading, from a data store, executable measurement unit determination software comprising a data filtration tool and a unit determination tool” and 3) “executing, by the at least one processor, the measurement unit determination software”, thus these computing components and steps are adding the words “apply it” with mere instructions to implement the abstract idea on a computer.
Additionally, the additional element step of 8) “outputting, by an input/output (I/O) interface to an I/O device, a graphical user interface of the second data structure in a display format” adds insignificant extra-solution activity/pre-solution activity in the form of WURC activity to the abstract idea. The following is an example of a court decision demonstrating computer functions as well-understood, routine and conventional activities, e.g. see MPEP 2106.05(d)(II): Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec – similarly, the current invention receives third structure data, and transmits the data to a device over a network, for example the Internet.
Mere instructions to apply an exception using generic computer components or insignificant extra-solution activity in the form of WURC activity cannot provide an inventive concept. The claims are not patent eligible (Step 2B: NO).
Claims 38-57 are therefore rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Steven G.S. Sanghera whose telephone number is (571)272-6873. The examiner can normally be reached M-F 7:30-5:00 (alternating Fri).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shahid Merchant can be reached at 571-270-1360. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/STEVEN G.S. SANGHERA/Primary Examiner, Art Unit 3684
