DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This communication is in response to the amendment received on 03/06/2026. Claims 1-2, 6-24 and 29-32 remain pending in this application.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-2, 6-24 and 29-32 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the enablement requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention.
In particular, claims 1, 9 and 17 have been amended to recite:
“initiating learning by the MRSC based on the feedback information element, wherein learning by the MRSC comprises:
(a) detecting via the OOMHP whether the feedback information element relates to the first indication or relates to the second indication; and
(b) storing via the OOMHP information relating to the detecting, wherein storing the information relating to the detecting enables the MRCS to facilitate customization of one or more communications of cluster-based information elements to the first electronic computer interface; and
in response to the initiating, reconfiguring the MRCS for the customization of the one or more communications of cluster-based information elements to the first electronic computer interface, wherein reconfiguring the MRCS comprises:
electronically writing new data to the electronic memory at the MRCS based on a result of the learning by the MRCS”.
It’s not clear nor described in the specification, how the system learns, and what type of machine-learning operation being used in the current application. The current specification recites “The system 200 will receive feedback from the treatment provided so that the system 200 can learn whether or not the suggested interventions were successful in reducing the risk of readmission. Additionally, the system 200 will learn from the accepted interventions and populate more of the successful interventions in future instances with further proven effectiveness.” in [0058], however, this subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention.
Claims 2, 6-8, 10-16, 18-24 and 29-32 incorporate the deficiencies of independent claims 1, 9 and 17, through dependency, and are also rejected.
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 1-2, 6-24 and 29-32 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.
As per claims 1, 9 and 17, it’s unclear what type of “learning” the medical records computer system use, in order to enable detecting whether the feedback information element relates to the first indication or relates to the second indication.
Claims 2, 6-8, 10-16, 18-24 and 29-32 incorporate the deficiencies of independent claims 1, 9 and 17, through dependency, and are 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 1-2 and 6-24 and 29-32 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.
Step 1:
Claims 1-2, 6-8, 21-24 and 31-32 are drawn to a non-transitory medium which is within the four statutory categories (i.e. manufacture). Claims 9-16 are drawn to a system which is within the four statutory categories (i.e. machine). Claims 17-20 and 29-30 are drawn to a method which is within the four statutory categories (i.e. process).
Step 2A, Prong 1:
As per independent claims, 1, 9 and 17, they have been amended now to recite:
“accessing, via at least one of the OOMHP associated with an electronic memory at a medical records computer system (MRCS), medical data elements for a pre-selected population;
identifying a portion of the medical data elements that are associated with a predetermined number of conditions, wherein the conditions are associated with a first admission and at least one readmission to a facility for at least one individual over a predetermined time period;
establishing a sample size based on the portion of the medical data elements;
identifying a correlation cluster, wherein identifying the correlation cluster comprises:
performing, via the OOMHP, a first-sequential pattern analysis on the portion of the medical data elements; and
determining that two or more of the conditions form the correlation cluster based on a frequency of co-occurrence of the two or more of the conditions;
in response to determining the correlation cluster based on the frequency of co-occurrence, generating and communicating, to a first electronic computer interface, a cluster-based information element that corresponds to a prediction for readmission and that is based on both the correlation cluster and the frequency of co-occurrence, wherein the cluster-based information element is transmitted to the first electronic computer interface via the OOMHP associated with the MRCS;
based on the transmitting, receiving: a feedback information element comprising (a) a first indication that content associated with the cluster-based information element was not accepted or (b) second indication that the content was accepted, and an indication of relevance of the content in relation to the readmission, wherein the indication of relevance identifies whether one or more interventions communicated via the cluster- based information element were successful in preventing the readmission;
initiating a learning by the MRCS based on the feedback information element, wherein the learning by the MRCS comprises:
(a) detecting via the OOMHP whether the feedback information element relates to the first indication or relates to the second indication; and
(b) storing via the OOMHP information relating to the detecting, wherein storing the information relating to the detecting enables the MRCS to facilitate customization of one or more communications of cluster-based information elements to the first electronic computer interface; and
in response to the initiating, reconfiguring the MRCS for the customization of the one or more communications of cluster-based information elements to the first electronic computer interface, wherein reconfiguring the MRCS comprises;
electronically writing new data to the electronic memory at the MRCS based on a result of the learning by the MRCS”.
These limitations are directed to an abstract idea of “certain methods of organizing human activity” based on managing personal behavior (user following rules and instructions) and interactions between people regarding determining a prediction for an individual’s readmission for a facility.
The mere nominal recitation of one or more generic computer processors (OOMHP) does not take the claims out of the methods of organizing human interactions grouping (current specification recites “well-known computing systems” to use as processors in par. 24).
Thus, the claims recite an abstract idea.
As per dependent claims, claim 8 recites “…based on a first readmission of the first individual for the at least one condition associated with the correlation cluster occurring, generate one or more interventional treatment options…”, “…generating at least one interventional treatment option”, and claim 11 recites “based on the notification that the first individual has been admitted and diagnosed, generating at least one interventional treatment option; and presenting the at least one interventional treatment option for the first individual to a first user, via the first electronic computer interface, for analysis by the first user”. These limitations correspond to an abstract idea of certain methods of organizing human activity, since they are directed to managing personal behavior and interactions between people regarding determining/generating treatment options based on the at least one condition associated with the correlation cluster occurring.
As per dependent claims, claim 2 recites “determining for the correlation cluster a support percentage, a confidence percentage, a correlation coefficient, or any combination of the support percentage, the confidence percentage, and the correlation coefficient”, claim 6 recites “…determining a regression coefficient and odds ratio after performing the first sequential pattern analysis,…”, which are directed to an abstract idea of mathematical concepts (mathematical relationships) (see MPEP 2106.04(a)(2)(I)).
Dependent claims 2, 6-8, 10-16, 18-24, 29-32 are ultimately dependent from claims 1, 9, 17 and include all the limitations of claims 1, 9, 17. Therefore, claims 2, 6-8, 10-16, 18-24, 29-32 recite the same abstract idea. Claims 2, 6-8, 10-16, 18-24, 29-32 describe a further limitation regarding the basis for determining a prediction for readmission of an individual to a facility after the first admission. These are all just further describing the abstract idea recited in claims 1, 9, 17, without adding significantly more.
After considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims do not amount to significantly more than the abstract idea itself.
Step 2A, Prong 2:
This judicial exception is not integrated into a practical application. In particular, claims recite the additional elements of “one or more hardware processors (OOMHP)”, “an electronic memory at a medical records computer system (MRCS)”, “one or more processors perform the steps of “identifying a portion of the medical data elements that are associated with a predetermined number of conditions, wherein the conditions are associated with a first admission and at least one readmission to a facility for at least one individual over a predetermined time period; establishing a sample size based on the portion of the medical data elements; identifying a correlation cluster, wherein identifying the correlation cluster comprises: (a) performing via the OOMHP, a first-sequential pattern analysis on the portion of the medical data elements; and determining that the two or more of the conditions form the correlation cluster is based on a frequency of co-occurrence of the two or more of the conditions; in response to determining the correlation cluster based on the frequency of co-occurrence, generating and communicating, to a first electronic computer interface, a cluster-based information element that corresponds to a prediction for readmission and that is based on both the correlation cluster and the frequency of co-occurrence, wherein: the cluster-based information element is transmitted to the first electronic computer interface via the OOMHP associated with the MRCS; based on the transmitting, receiving: a feedback information element comprising (a) a first indication that content associated with the cluster-based information element was not accepted or (b) a second indication that the content was accepted, and an indication of relevance of the content in relation to the readmission, wherein the indication of relevance identifies whether one or more interventions communicated via the cluster- based information element were successful in preventing the readmission; initiating a learning by the MRCS based on the feedback information element, wherein learning by the MRCS comprises: (a) detecting via the OOMHP whether the feedback information element relates to the first indication or relates to the second indication; and (b) storing via the OOMHP information relating to the detecting, wherein storing the information relating to the detecting enables the MRCS to facilitate customization of one or more communications of cluster-based information elements to the first electronic computer interface; and; in response to the initiating, reconfiguring the MRCS for the customization of the one or more communications of cluster-based information elements to the first electronic computer interface, wherein reconfiguring the MRCS comprises; electronically writing new data to the electronic memory at the MRCS based on a result of the learning by the MRCS” (claims 1, 9 and 17).
These are hardware and software elements, these limitations are not enough to qualify as “practical application” being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of the abstract idea in a particular technological environment, and mere instructions to apply/implement/automate an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular field or technological environment do not provide practical application for an abstract idea (MPEP 2106.05(f) & (h)).
This feature corresponds to an additional element that corresponds to mere instructions to apply/implement/automate an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular field or technological environment do not provide practical application for an abstract idea. The current specification recites “The system 200 will receive feedback from the treatment provided so that the system 200 can learn whether or not the suggested interventions were successful in reducing the risk of readmission. Additionally, the system 200 will learn from the accepted interventions and populate more of the successful interventions in future instances with further proven effectiveness.” in [0058]. Therefore, the system uses the suggested interventions and feedbacks from the users to facilitate a customization of the intervention suggestions (for the future), which is only a result-oriented solution. These additional elements are mere instructions to apply an exception, because they recite no more than an idea of a solution or outcome (see MPEP 2106.05(f)).
Claims also recite other additional limitations beyond abstract idea, including functions such as accessing/storing/updating data from/to a database and communicating/transmitting data, these functions are insignificant extra-solution activities (see MPEP 2106.05 (g)), which do not provide a practical application for the abstract idea.
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 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 element of using a computer server/one or more hardware processors to perform both the identifying and determining steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
In particular, the feature of “establishing a sample size portion of the data elements”, or “static data sampling for sequence mining” is a well-understood, routine and conventional activity known in the field, as evidenced by the article published on Seventh IEEE International Conference on Data Mining by Raissi et al. (“Sampling for Sequential Pattern Mining: From Static Databases to Data Streams”, published in 2007-Cited on PTO-892-Referenced Cited).
Additionally, using “a first-sequential pattern analysis” to determine two or more conditions to form a correlation cluster is a well-understood, routine and conventional activity, as evidenced by the article provided in the previous communication, that is “Readmission prediction using deep learning on electronic health records” by Ashfaq et al. (“sequential modeling” on page 2 and “readmission analysis” on page 5).
Accordingly, “a first-sequential pattern analysis” to determine two or more conditions to form a correlation cluster is a well-understood, routine and conventional activity known in the industry and claims are directed to mere instruction to apply an exception.
Therefore, claims 1-2, 6-28 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Response to Arguments
Applicant's arguments filed 03/06/2026 have been fully considered but they are not persuasive. Applicant’s arguments will be addressed below in the order in which they appear.
Arguments about 35 USC 101 rejection:
Arguments about step 2A, prong one rejection: Applicant argues that claims do not recite a human, and do not recite a method of organizing an activity of the human and rather than organizing the activity of a human, the activity of machine and machine-learning elements is organized.
In response, Examiner submits that machine learning elements are not part of the abstract idea, but correspond to additional elements that are hardware and software elements. Examiner also submits that the claim limitations are directed to an abstract idea of certain methods of organizing human activity based on managing personal behavior (user following rules and instructions) and interactions between people regarding determining a prediction for readmission for an individual, with a recitation of generic computing components, not because any part of the claims recite a human). The MPEP recites “…the sub-groupings encompass both activity of a single person…and an activity involves multiple people…and thus, certain activity between a person and a computer…may fall within the “certain methods of organizing human activity” grouping” (MPEP 2106.04(a)(2) II). These claim limitations are directed to an abstract idea of certain methods of organizing human activity, which includes user following rules and instructions using generic hardware processors.
Arguments about step 2A, prong two rejection: Applicant argues that claims include additional elements that in combination with other claim elements integrate the purported judicial exception into a practical application. The additional elements, individually or in combination, amount to significantly more than the judicial exception. Applicant argues that reconfiguring the medical records computer, in response to the machine learning algorithm based on the feedback information elements by electronically writing new data to the electronic memory based on the results of the initiating provides practical application.
In response, Examiner submits that updating the electronic memory by electronically writing new data, based on the feedback information and based on data from the learning algorithm corresponds to mere instructions to apply/implement/automate an abstract idea in a particular technological environment and do not provide a practical application (see the rejection above).
Arguments about step B rejection: Applicant argues that claims are directed to an improvement in the technology, since the claims recite “initiating learning by the MRCS based on feedback information element amount to more than generally linking use of a judicial exemption to a field of use.
In response, Examiner submits that the feature of “establishing a sample size portion of the data elements”, or “static data sampling for sequence mining” is a well-understood, routine and conventional activity known in the field, as evidenced by the article published on Seventh IEEE International Conference on Data Mining by Raissi et al. (“Sampling for Sequential Pattern Mining: From Static Databases to Data Streams”, published in 2007-Cited on PTO-892-Referenced Cited).
Additionally, using “a first-sequential pattern analysis” to determine two or more conditions to form a correlation cluster is a well-understood, routine and conventional activity, as evidenced by the article provided in the previous communication, that is “Readmission prediction using deep learning on electronic health records” by Ashfaq et al. (“sequential modeling” on page 2 and “readmission analysis” on page 5). Accordingly, “a first-sequential pattern analysis” to determine two or more conditions to form a correlation cluster is a well-understood, routine and conventional activity known in the industry and claims are directed to mere instruction to apply an exception.
Arguments about 35 USC 112(a) rejection: The 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph rejection, as claims failing to comply with the written description requirement has been withdrawn in light of the amendments. However, upon further consideration, a new ground(s) of rejection is made in view of 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the enablement requirement.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/DILEK B COBANOGLU/Primary Examiner, Art Unit 3687
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