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 .
Claim Status
Claims 1-20 are pending.
Claims 1-20 are rejected.
Response to Arguments
Allowable Subject Matter: Applicant has fail to amend the independent claim to include the entirety of the indicated allowable subject matter; therefore, the claims are not allowable.
101 Rejection: Applicant argues the claim limitation “generating, using the first predictive model, a plurality of code predictions for the plurality or codes” is patentable subject matter. Examiners disagrees because this limitation recites an abstract idea (mathematical calculation).
103 Rejection: Applicant’s arguments with respect to claims 1-20 have been fully considered and are
persuasive. Upon further consideration, and in view of applicant’s amendments, a new grounds of
rejection is made in view of newly cited reference Behlmann.
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, 4-12, 14-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The following is Examiner's analysis of the claimed invention under the 2019 Revised Patent Subject Matter Eligibility Guidance (PEG)
STEP 1 ls the claim to a Process, Machine, Manufacture or Composition of matter? Yes. Claim 1 recites a process (method), claim 11 recites a machine (system), claim 17 recites a manufacture (computer-readable media).
STEP2A Prone one: Does The Claim Recite An Abstract Idea, Law Of Nature, or Natural Phenomenon? Yes. Claim 1 (and similar claims 11 and 17) recites “generating, by the one or more processors and using a first predictive model, a scaled risk score for the entity based on the first set of binary coded attributes, wherein generating the scaled risk score using the first predictive model comprises: generating a plurality of code predictions for the plurality of codes, respectively, and a simulated engagement score for the entity based on the second set of categorical attributes, generating a risk score for the entity based on an aggregation of the plurality of code predictions and the simulated engagement score, and applying a first scaling coefficient to the risk score to generate the scaled risk score; generating, by the one or more processors and using a second predictive model, a scaled event score for the entity based on the second set of categorical attributes; generating, by the one or more processors, a cohort score for the entity cohort file based on the scaled risk score, the scaled event score, and the subset of target entities” which falls within the mathematical concepts grouping of abstract ideas.
The steps of generating a scaled risk score, scaled event score, cohort score cover performance of a mathematical calculation, and therefore, the claim recites an abstract idea.
STEP2A Prone two: Does The Claim Recite Additional Elements That Integrate The Judicial Exception Into A Practical Application? No. Claim 1 recites “a computer-implemented method comprising” which amounts to merely including instructions to implement an abstract idea on a computer.
Claim 11 recites “a system comprising: one or more processors; and one or more memories storing processor-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising” which amounts to merely including instructions to implement an abstract idea on a computer.
Claim 17 recites “one or more non-transitory computer-readable media storing processor-executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising” which amounts to merely including instructions to implement an abstract idea on a computer.
Claim 1 (and similar claims 11 and 17) recites “receiving, by one or more processors, an entity cohort file that identifies a plurality of entity attributes for an entity within an entity cohort, wherein the plurality of entity attributes comprises a first set of binary coded attributes corresponding to a plurality of codes defined within a coding domain and a second set of categorical attributes; extracting, by the one or more processors, a cohort-level optimization dataset from the entity cohort file that identifies a subset of target entities from the entity cohort that comprises the entity” which is mere necessary data gathering.
Claim 1 (and similar claims 11 and 17) recites “and storing, by the one or more processors, a compressed entity cohort file that identifies the cohort score, the subset of target entities, and an entity-level score for each entity within the subset of target entities” which is insignificant-extra solution activity tangentially related to the invention. Adding a final step of storing data does not add a meaningful limitation to the judicial exception, and therefore, the additional element is insignificant-extra solution activity.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. The claims recite mere instructions to implement an abstract idea on a computer. The courts have determined merely including instructions to implement the abstract idea on a computer does not qualify as “significantly more” when recited in a claim with a judicial exception (See Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984).
The claims recites mere necessary data gathering. The courts have determined mere data gathering to not be enough to qualify as “significantly more” when recited in a claim with a judicial exception (See CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011)).
Claim 1 (and similar claims 11 and 17) recites “and storing, by the one or more processors, a compressed entity cohort file that identifies the cohort score, the subset of target entities, and an entity-level score for each entity within the subset of target entities”. The courts have determined storing and retrieving information in memory is well-understood, routine, and conventional functionality when claimed in a merely generic manner (see Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015)).
There is no indication that the elements of the claim, individually nor in combination, integrate the judicial exception into a practical application or amount to significantly more than the judicial exception.
For the reasons above, claims 1, 11, and 17 are rejected as being directed to nonpatentable
subject matter under §101. This rejection applies equally to the dependent claims (except claims 3 and 13). The additional limitations of the dependent claims are addressed briefly below:
Regarding claims 2 and 12
STEP 1 ls the claim to a Process, Machine, Manufacture or Composition of matter? Yes. Claim 2 recites a process (method), claim 12 recites a machine (system).
STEP2A Prone one: Does The Claim Recite An Abstract Idea, Law Of Nature, or Natural Phenomenon? Yes. The claims inherits the abstract idea of the parent claim.
STEP2A Prone two: Does The Claim Recite Additional Elements That Integrate The Judicial Exception Into A Practical Application? No. The claims recite “wherein the compressed entity cohort file is stored in association with a plurality of compressed entity cohort files respectively corresponding to a plurality of entity cohorts, and the computer-implemented method further comprises: initiating a presentation of a selection interface to a user that comprises a plurality of selectable icons respectively corresponding to the plurality of entity cohorts” which is insignificant-extra solution activity tangentially related to the invention. Adding a final step of “initiating a presentation of a selection interface” does not add a meaningful limitation to the judicial exception, and therefore, the additional element is insignificant-extra solution activity.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. The claims recite “wherein the compressed entity cohort file is stored in association with a plurality of compressed entity cohort files respectively corresponding to a plurality of entity cohorts, and the computer-implemented method further comprises: initiating a presentation of a selection interface to a user that comprises a plurality of selectable icons respectively corresponding to the plurality of entity cohorts” which is receiving and transmitting data over a network. The courts have determined receiving and transmitting data over a network is well‐understood, routine, and conventional functionality when claimed in a merely generic manner (see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362).
Regarding claims 3 and 13
STEP 1 ls the claim to a Process, Machine, Manufacture or Composition of matter? Yes. Claim 3 recites a process (method), claim 13 recites a machine (system).
STEP2A Prone one: Does The Claim Recite An Abstract Idea, Law Of Nature, or Natural Phenomenon? Yes. The claims inherits the abstract idea of the parent claim.
STEP2A Prone two: Does The Claim Recite Additional Elements That Integrate The Judicial Exception Into A Practical Application? Yes. The claims recite “receiving location data associated with a user of the selection interface; identifying a portion of the plurality of entity cohorts based on the location data; and modifying the selection interface to adjust a focus to the portion of the plurality of entity cohorts” which integrates the judicial exception into the technological improvement disclosed in the specification (Para 0064, the selection interface may leverage one or more geospatial algorithms to generate travel times, optimal routes, and/or the like to identify a set of reachable entities within an operational time period).
Regarding claims 4 and 14
STEP 1 ls the claim to a Process, Machine, Manufacture or Composition of matter? Yes. Claim 4 recites a process (method), claim 14 recites a machine (system).
STEP2A Prone one: Does The Claim Recite An Abstract Idea, Law Of Nature, or Natural Phenomenon? Yes. The claims inherits the abstract idea of the parent claim.
STEP2A Prone two: Does The Claim Recite Additional Elements That Integrate The Judicial Exception Into A Practical Application? No. The claims recite “arranging the plurality of selectable icons within the selection interface based on the cohort score, wherein the plurality of selectable icons is arranged in accordance with a magnitude of each of a plurality of cohort scores respectively corresponding to the plurality of entity cohorts” which falls within the mathematical concepts grouping of abstract ideas.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. There is no indication that the elements of the claim, individually nor in
combination, integrate the judicial exception into a practical application or amount to significantly more than the judicial exception.
Regarding claims 5 and 15
STEP 1 ls the claim to a Process, Machine, Manufacture or Composition of matter? Yes. Claim 5 recites a process (method), claim 15 recites a machine (system).
STEP2A Prone one: Does The Claim Recite An Abstract Idea, Law Of Nature, or Natural Phenomenon? Yes.
STEP2A Prong two: Does The Claim Recite Additional Elements That Integrate The Judicial Exception Into A Practical Application? No. The claims recite “wherein the plurality of code predictions is generated using a first branch of the first predictive model, the simulated engagement score is generated using a second branch of the first predictive model, the risk score is generated using an aggregation layer of the first predictive model, and the first scaling coefficient is applied to the risk score to generate the scaled risk score using a scaling layer of the first predictive model” which amounts to merely including instructions to implement an abstract idea on a computer.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. There is no indication that the elements of the claim, individually nor in
combination, integrate the judicial exception into a practical application or amount to significantly more than the judicial exception.
Regarding claims 6 and 16
STEP 1 ls the claim to a Process, Machine, Manufacture or Composition of matter? Yes. Claim 6 recites a process (method), claim 16 recites a machine (system).
STEP2A Prone one: Does The Claim Recite An Abstract Idea, Law Of Nature, or Natural Phenomenon? Yes. The claims inherits the abstract idea of the parent claim.
STEP2A Prone two: Does The Claim Recite Additional Elements That Integrate The Judicial Exception Into A Practical Application? No. The claims recite “generating a code prediction of the plurality of code predictions for a code of the plurality of codes comprises: determining, using the routing logic, a processing route for the code; and responsive to the processing route identifying the machine learned prediction model, inputting a third set of historical attributes for the entity to the machine learned prediction model to receive the code prediction” which is mere necessary data gathering.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. The courts have determined mere data gathering to not be enough to qualify as “significantly more” when recited in a claim with a judicial exception (See CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011)).
Regarding claims 7
STEP 1 ls the claim to a Process, Machine, Manufacture or Composition of matter? Yes. The claim recites a process (method).
STEP2A Prone one: Does The Claim Recite An Abstract Idea, Law Of Nature, or Natural Phenomenon? Yes. Claim 7 recites “wherein the first branch of the first predictive model further comprises a normalization layer and generating the code prediction further comprises normalizing the code prediction based on a code prediction distribution comprising a respective code prediction for each entity within the entity cohort” which falls within the mathematical concepts grouping of abstract ideas.
STEP2A Prong two: Does The Claim Recite Additional Elements That Integrate The Judicial Exception Into A Practical Application? No. There is no indication that the elements of the claim
integrate the judicial exception into a practical application.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. There is no indication that the elements of the claim, individually nor in
combination, integrate the judicial exception into a practical application or amount to significantly more than the judicial exception.
Regarding claims 8 and 18
STEP 1 ls the claim to a Process, Machine, Manufacture or Composition of matter? Yes. Claim 8 recites a process (method), claim 18 recites a manufacture (computer-readable media).
STEP2A Prone one: Does The Claim Recite An Abstract Idea, Law Of Nature, or Natural Phenomenon? Yes. The claims recite “wherein generating the scaled event score for the entity based on the second set of categorical attributes comprises: generating, using the second predictive model, an event prediction for the entity based on the second set of categorical attributes; and applying a second scaling coefficient to the event prediction to generate the scaled event score” which falls within the mathematical concepts grouping of abstract ideas.
STEP2A Prone two: Does The Claim Recite Additional Elements That Integrate The Judicial Exception Into A Practical Application? No. There is no indication that the elements of the claim
integrate the judicial exception into a practical application.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. There is no indication that the elements of the claim, individually nor in
combination, integrate the judicial exception into a practical application or amount to significantly more than the judicial exception.
Regarding claims 9 and 19
STEP 1 ls the claim to a Process, Machine, Manufacture or Composition of matter? Yes. Claim 9 recites a process (method), claim 19 recites a manufacture (computer-readable media).
STEP2A Prone one: Does The Claim Recite An Abstract Idea, Law Of Nature, or Natural Phenomenon? Yes. The claims inherits the abstract idea of the parent claim.
STEP2A Prone two: Does The Claim Recite Additional Elements That Integrate The Judicial Exception Into A Practical Application? No. The claims recite “wherein second predictive model comprises a graph-based causal model with a plurality of nodes that correspond to the second set of categorical attributes” which merely applies the judicial exception into the technical field of graph databases.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. The courts have determined merely indicating a field of use in which to apply a judicial exception does not amount to significantly more than the judicial exception (see Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981)).
Regarding claims 10 and 20
STEP 1 ls the claim to a Process, Machine, Manufacture or Composition of matter? Yes. Claim 10 recites a process (method), claim 20 recites a manufacture (computer-readable media).
STEP2A Prone one: Does The Claim Recite An Abstract Idea, Law Of Nature, or Natural Phenomenon? Yes. The claim recites “wherein the risk score is a first data type, and the event score is a second data type that is incompatible with the first data type, and the first scaling coefficient and the second scaling coefficient are defined by a compatibility ruleset for transforming the first data type and the second data type to a compatible data type” which falls within the mathematical concepts grouping of abstract ideas.
STEP2A Prong two: Does The Claim Recite Additional Elements That Integrate The Judicial Exception Into A Practical Application? No. There is no indication that the elements of the claim
integrate the judicial exception into a practical application.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No. There is no indication that the elements of the claim, individually nor in
combination, integrate the judicial exception into a practical application or amount to significantly more than the judicial exception.
Taken alone, the additional elements of the dependent claims (except claims 3 and 13) do not amount to significantly more than the above-identified judicial exception (the abstract idea). 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.
Claim Rejections - 35 USC § 103
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.
Claims 1-5, 11-15, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Fogel et al (US 20170177822 A1) hereafter Fogel in view of Breen et al (US 20210240556 A1) hereafter Breen further in view of Behlmann et al (US 20240006060 A1) hereafter Behlmann
Regarding claim 1, Fogel a computer-implemented method comprising: receiving, by one or more processors, an entity cohort file that identifies a plurality of entity attributes for an entity within an entity cohort, wherein the plurality of attributes comprises a first set of binary coded attributes and a second set of categorical attributes (Para 0212, The database comprises variables with values that are binary, categorical, or ordinal, or real numbers); extracting, by the one or more processors, a cohort-level optimization dataset from the entity cohort file that identifies a subset of target entities from the entity cohort that comprises the entity (Para 0177, Generating personalized prognostic profiles is achieved by using large and efficient databases can be managed and with which predictive models can be estimated, validated, and applied) (“personalized prognostic profiles” teaches “subset of target entities”).
Fogel does not appear to explicitly teach generating, by the one or more processors and using a first predictive model, a scaled risk score for the entity based on the first set of binary coded attributes; generating, by the one or more processors and using a second predictive model, a scaled event score for the entity based on the second set of categorical attributes; generating, by the one or more processors, a cohort score for the entity cohort file based on the scaled risk score, the scaled event score, and the subset of target entities; and storing, by the one or more processors, a compressed entity cohort file that identifies the cohort score, the subset of target entities, and an entity-level score for each entity within the subset of target entities.
In analogous art, Breen teaches generating, by the one or more processors and using a first predictive model, a scaled risk score for the entity based on the first set of binary coded attributes (Para 0069, The first predicted confidence score indicates the binary classification model's predicted certainty of the corresponding member's likelihood of having additional insurance); generating, by the one or more processors and using a second predictive model, a scaled event score for the entity based on the second set of categorical attributes (Para 0080, With multi-class classification models, the output of the one or more multi-class classification models is an insurer name, an insurance product, an insurance plan, and/or the like); generating, by the one or more processors, a cohort score for the entity cohort file based on the scaled risk score, the scaled event score, and the subset of target entities (Para 0087, the prediction platform 100 (e.g., via an analytic computing entity 65) can determine whether the API-based eligibility response confirms that the member is a member of the insurer); and storing, by the one or more processors, a compressed entity cohort file that identifies the cohort score, the subset of target entities, and an entity-level score for each entity within the subset of target entities (Para 0088, At step/operation 536 of FIG. 5B, the prediction platform 100 can store the parsed or extracted information/data comprising member information/data and/or insure information/data). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Fogel to include the teaching of Breen. One of ordinary skill in the art would be motivated to implement this modification in order to automate data processing, as taught by Breen (Abs, Methods, apparatus, systems, computing devices, computing entities, and/or the like for verifying the coordination of benefits information with an end-to-end automated process).
Fogel in view of Breen does not appear to explicitly teach wherein generating the scaled risk score using the first predictive model comprises: generating a plurality of code predictions for the plurality of codes, respectively, and a simulated engagement score for the entity based on the second set of categorical attributes, generating a risk score for the entity based on an aggregation of the plurality of code predictions and the simulated engagement score, and applying a first scaling coefficient to the risk score to generate the scaled risk score.
In analogous art, Behlmann teaches wherein generating the scaled risk score using the first predictive model comprises: generating a plurality of code predictions for the plurality of codes, respectively, and a simulated engagement score for the entity based on the second set of categorical attributes, generating a risk score for the entity based on an aggregation of the plurality of code predictions and the simulated engagement score, and applying a first scaling coefficient to the risk score to generate the scaled risk score (Para 0050, risk score (e.g., the relative risk of the member for the next 12 months compared to other plan members with respect to total cost), inpatient stay probability, er risk score (e.g., the likelihood that the member will have 1 or more ER visits in the next 12 months), nest score, engagement score). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Fogel in view of Breen to include the teaching of Behlmann. One of ordinary skill in the art would be motivated to implement this modification in order to classify data, as taught by Behlmann (Abs, a machine learning (ML) model configured to automatically classify the data by admission type).
Regarding claim 2, Fogel in view of Breen further in view of Behlmann teaches the computer-implemented method further comprises: initiating a presentation of a selection interface to a user that comprises a plurality of selectable icons respectively corresponding to the plurality of entity cohorts, and wherein the compressed entity cohort file is stored in association with a plurality of compressed entity cohort files respectively corresponding to a plurality of entity cohorts (Fogel, Para 0066, The relationship of time and survival can be shown as a curve, a bar chart, a column chart, or a pattern of icons).
Regarding claim 3, Fogel in view of Breen further in view of Behlmann teaches the computer-implemented method of claim 2, further comprising: receiving location data associated with a user of the selection interface; identifying a portion of the plurality of entity cohorts based on the location data; and modifying the selection interface to adjust a focus to the portion of the plurality of entity cohorts (Fogel, Para 0096, Likewise, the reference database of potentially predictive variables may include, in addition to demographic factors, variables related to the geographical location, physical and social environment of the person of interest, the setting or system of care).
Regarding claim 4, Fogel in view of Breen further in view of Behlmann teaches the computer-implemented method of claim 2, further comprising: arranging the plurality of selectable icons within the selection interface based on the cohort score, wherein the plurality of selectable icons is arranged in accordance with a magnitude of each of a plurality of cohort scores respectively corresponding to the plurality of entity cohorts (Breen, Para 0089, the user interface 800 can be dynamically updated to show the most current priority order of claims, for example, assigned to a user at any given time). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Fogel to include the teaching of Breen. One of ordinary skill in the art would be motivated to implement this modification in order to automate data processing, as taught by Breen (Abs, Methods, apparatus, systems, computing devices, computing entities, and/or the like for verifying the coordination of benefits information with an end-to-end automated process).
Regarding claim 5, Fogel in view of Breen further in view of Behlmann teaches the computer-implemented method of claim 1, wherein the plurality of code predictions is generated using a first branch of the first predictive model, the simulated engagement score is generated using a second branch of the first predictive model, the risk score is generated using an aggregation layer of the first predictive model, and the first scaling coefficient is applied to the risk score to generate the scaled risk score using a scaling layer of the first predictive model (Para 0050, risk score (e.g., the relative risk of the member for the next 12 months compared to other plan members with respect to total cost), inpatient stay probability, er risk score (e.g., the likelihood that the member will have 1 or more ER visits in the next 12 months), nest score, engagement score). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Fogel in view of Breen to include the teaching of Behlmann. One of ordinary skill in the art would be motivated to implement this modification in order to classify data, as taught by Behlmann (Abs, a machine learning (ML) model configured to automatically classify the data by admission type).
Claim 11 is the system claim corresponding to the method claim 1, and is analyzed and rejected accordingly.
Claim 12 is the system claim corresponding to the method claim 2, and is analyzed and rejected accordingly.
Claim 13 is the system claim corresponding to the method claim 3, and is analyzed and rejected accordingly.
Claim 14 is the system claim corresponding to the method claim 4, and is analyzed and rejected accordingly.
Claim 15 is the system claim corresponding to the method claim 5, and is analyzed and rejected accordingly.
Claim 17 is the computer-readable media claim corresponding to the method claim 1, and is analyzed and rejected accordingly.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Brooks Hale whose telephone number is 571-272-0160. The examiner can normally be reached 9am to 5pm est.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sanjiv Shah can be reached on (571) 272-4098. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/B.T.H./Examiner, Art Unit 2166
/SANJIV SHAH/Supervisory Patent Examiner, Art Unit 2166
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