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 .
Response to Amendment
The amendment, filed 12/29/2025, has been entered. The examiner notes claims 1-22 are pending with claims 5-9 and 11-21 withdrawn from further consideration.
Response to Arguments
Applicant’s arguments, see Remarks page 7, filed 12/29/2025, with respect to the claim objections to claims 1 and 10 have been fully considered and are persuasive. The applicant has amended the claims to overcome the claim objections. The claim objections to claims 1 and 10 have been withdrawn.
Applicant’s arguments, see Remarks pages 7-9, filed 12/29/2025, with respect to the rejection(s) of claim(s) 1-4, 10, and 22 under 35 USC 102 and 103 have been fully considered and are persuasive. The examiner agrees that the prior art used in the previous office action fails to teach the newly amended limitations now present within the claims. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Wasson (US 20160345872 A1), Ma (US 20170188841 A1), and Conroy (US 20180307995 A1).
Applicant's arguments, see Remarks pages 9-11, filed 12/29/2025, with respect to the rejection claim(s) 1-4, 10, and 22 under 35 USC 101 have been fully considered but they are not persuasive.
In response to the applicant’s argument that the claims are allegedly eligible subject matter at step 2A prong 1 of the Alice/Mayo test, the examiner respectfully disagrees. The examiner notes that the steps of “acquiring” data using a sensor and training the model are pre-solution activities and not part of the abstract idea. The abstract idea within the claims is the “applying a model” and “deriving…the physiological rank” steps. As mentioned in the previous office action, applicant’s specification para. [00234] states that “The model may include a machine learning model”. Machine learning is the use and development of computer systems that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyze and draw inferences from patterns in data that is known to those of ordinary skill in the art. The examiner further contends that the “deriving” step within the claims is a mental process capable of being performed in the human mind, with an example provided below in the 35 USC 101 rejections. Thus, the steps that form the abstract idea are drawn to both a mental process and mathematical concept, which fall within the “abstract idea” grouping and consequently not eligible subject matter at step 2A prong 1.
In response to the applicant’s argument that the claims are eligible subject matter at step 2A prong 2, the examiner respectfully disagrees. The examiner notes that both the “applying” a model step and deriving step are merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f). Thus, the examiner notes that the claims remain ineligible subject matter at step 2A prong 2.
In response to the applicant’s argument that the claims are eligible subject matter at step 2B, the examiner respectfully disagrees. As discussed above, the “acquiring” data from a sensor and training a model are pre-solution activities. Even if one would interpret that “apply” step and the “deriving” step as being implemented by one of the additional elements (of which the examiner notes there is no evidence of this from the current claim language as the claims merely use “apply it” or similar language as discussed above), the additional elements were found to be well-understood, routine, and conventional and thus do not qualify as “significantly more”.
Therefore, for the reasons provided above, the 35 USC 101 rejection of claims 1-4, 10, and 22 is maintained.
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 1-4, 10, and 22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent Claim 1 recites:
A computer-implemented method for deriving a physiological rank indicative of a physiological status of a user wearing a wearable device, the computer-implemented method comprising:
acquiring, from a sensor on the wearable device worn by a user, data including bodily parameter data related to the user, the sensor comprising an optical sensing module including a plurality of lasers configured to emit light into the user's skin and a photodetector array configured to collect back-scattered light to form the bodily parameter data;
applying a model to the bodily parameter data by generating a delta spectrum by subtracting baseline data from the bodily parameter data, the baseline data comprising an average of bodily parameter data acquired from the user over a predefined period of time; and
deriving, from the physiological information output by the model, the physiological rank indicative of the physiological status of the user wearing the device, wherein:
the physiological rank is a given value on a physiological rank scale;
the model is trained against bodily parameter data being associated with a clinical label derived from outputs of one or more standard point-of-care tests.
Independent Claim 10 recites:
A computer-implemented method for deriving a physiological rank indicative of a physiological status of a user, the computer-implemented method comprising:
applying a model to bodily parameter data acquired from a sensor on a wearable device worn by a user to obtain physiological information related to the user, the sensor comprising an optical sensing module including a plurality of lasers configured to emit light into the user's skin and a photodetector array configured to collect back-scattered light to form the bodily parameter data, the model trained against bodily parameter data being associated with a clinical label derived from outputs of one or more standard point-of-care tests; and
deriving, from the physiological information output from the model, the physiological rank indicative of the physiological status of the user wearing the wearable device, wherein the physiological rank is a value on a physiological rank scale.
Step 1:
The examiner finds independent claims 1 and 10 drawn to method steps.
Step 2A Prong 1:
The above claim limitations constitute an abstract idea that is part of the Mathematical Concepts and/or Mental Processes group identified in the 2019 Revised Patent Subject Matter Eligibility Guidance published in the Federal Register (84 FR 50) on January 7, 2019.
“A mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words ….” October 2019 Update: Subject Matter Eligibility, II. A. i. “[T]here are instances where a formula or equation is written in text format that should also be considered as falling within this grouping.” Id. at II. A. ii. “[A] claim does not have to recite the word “calculating” in order to be considered a mathematical calculation.” Id. at II. A. iii. See for example, SAP Am., Inc. v. Investpic, LLC, 898 F.3d 1161, 1163-65 (Fed. Cir. 2018).
The claimed steps of acquiring, applying, and deriving recite mental processes and mathematical concepts (i.e., mathematical relationships, mathematical formulas or equations, and mathematical calculations).
The step of “acquiring” data in independent Claims 1 and 10 is a mere data gathering step that utilizes a computational device. The steps of “applying a model” to data is a mathematical calculation to determine a relationship between data and group them. For example, in paragraph [00234] of applicant’s specification, the applicant states “The model may include a machine learning model”. Machine learning is the use and development of computer systems that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyze and draw inferences from patterns in data that is known to those of ordinary skill in the art. The step of “deriving” a physiological rank in claims 1 and 10 is a mental process capable of being performed by the human mind. For example, the human mind is capable of deriving the meaning of an unknown word from its context.
The claimed steps of acquiring, applying, and deriving can be practically performed in the human mind using mental steps or basic critical thinking, which are types of activities that have been found by the courts to represent abstract ideas.
“[T]he ‘mental processes’ abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.” MPEP 2106.04(a)(2) III. The pending claims merely recite steps for estimation that include observations, evaluations, and judgments.
Examples of ineligible claims that recite mental processes include:
• a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind,
Electric Power Group, LLC v. Alstom, S.A.;
• claims to “comparing BRCA sequences and determining the existence of alterations,” where the claims cover any way of comparing BRCA sequences such that the comparison steps can practically be performed in the human mind,
University of Utah Research Foundation v. Ambry Genetics Corp.
• a claim to collecting and comparing known information, which are steps that can be practically performed in the human mind, Classen Immunotherapies, Inc. v. Biogen IDEC.
See p. 7-8 of October 2019 Update: Subject Matter Eligibility.
Regarding the dependent claims 2-4 and 22, the dependent claims are directed to either 1) steps that are also abstract or 2) additional data output that is well-understood, routine and previously known to the industry. Although the dependent claims are further limiting, they do not recite significantly more than the abstract idea. A narrow abstract idea is still an abstract idea and an abstract idea with additional well-known equipment/functions is not significantly more than the abstract idea.
Step 2 A Prong 2:
This judicial exception (abstract idea) in Claims 1-4, 10, and 22 is not integrated into a practical application because:
• The abstract idea amounts to simply implementing the abstract idea on a computing device. For example, the recitations regarding the generic computing components for acquiring, applying, and deriving merely invoke a computer as a tool.
• The data-gathering step (acquiring) and the data-output step do not add a meaningful limitation to the method as they are insignificant extra-solution activity.
• There is no improvement to a computer or other technology. “The McRO court indicated that it was the incorporation of the particular claimed rules in computer animation that "improved [the] existing technological process", unlike cases such as Alice where a computer was merely used as a tool to perform an existing process.” MPEP 2106.05(a) II. The claims recite a computing device that is used as a tool for acquiring, applying, and deriving.
• The claims do not apply the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition. Rather, the abstract idea is utilized to determine a relationship among data to estimate bio-information.
• The claims do not apply the abstract idea to a particular machine. “Integral use of a machine to achieve performance of a method may provide significantly more, in contrast to where the machine is merely an object on which the method operates, which does not provide significantly more.” MPEP 2106.05(b). II. “Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more.” MPEP 2106.05(b) III. The pending claims utilize a computing device for acquiring, applying, and deriving. The claims do not apply the obtained prediction to a particular machine. Rather, the data is merely output in a post-solution step.
Step 2B:
The additional elements are identified as follows: sensor, wearable device, and processor.
Those in the relevant field of art would recognize the above-identified additional elements as being well-understood, routine, and conventional means for data-gathering and computing, as demonstrated by
• Applicant’s specification (e.g. paragraph [0029]) which discloses that the wearable device may be any device worn on the body that are well-understood, routine, and conventional activities previously known to the pertinent industry;
• Applicant’s specification (e.g. paragraphs 00141-00143) which disclose the processor in a general manner and performing general functions that are well-understood, routine, and conventional activities previously known to the pertinent industry;
• The additional element of a "the sensor comprisinq an optical sensinq module includinq a plurality of lasers confiqured to emit liqht into the user's skin and a photodetector array confiqured to collect back-scattered liqht to form the bodily parameter data" is considered a concept which is well-known, routine, and conventional, as known from Bourquin (US 20200193121 A1) which discloses in para. 0003 “The emission of light into targeted tissue (or skin; both being used herein as meaning the same) is most commonly done by one or more LEDs or laser diodes (as light source), and the collection of light is most commonly done directly using a photosensor (as light sensor, such as a photodiode)…”;
• Applicant’s Background in the specification
Thus, the claimed additional elements “are so well-known that they do not need to be described in detail in a patent application to satisfy 35 U.S.C. § 112(a).” Berkheimer Memorandum, III. A. 3.
Furthermore, the court decisions discussed in MPEP § 2106.05(d)(lI) note the well-understood, routine and conventional nature of such additional generic computer components as those claimed. See option III. A. 2. in the Berkheimer memorandum.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the units associated with the steps do not add meaningful limitation to the abstract idea. A computer, processor, memory, or equivalent hardware is merely used as a tool for executing the abstract idea(s). The process claimed does not reflect an improvement in the functioning of the computer.
When considered in combination, the additional elements (i.e. the generic computer functions and conventional equipment/steps) do not amount to significantly more than the abstract idea. Looking at the claim limitations as a whole 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
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.
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 1-2, 10, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Akhbardeh (US 20220160256 A1) in view of Wasson (US 20160345872 A1), Ma (US 20170188841 A1), and Conroy (US 20180307995 A1).
Regarding claim 1, Akhbardeh teaches a computer-implemented method for deriving a physiological rank indicative of a physiological status of a user wearing a wearable device, the computer-implemented method comprising:
acquiring, from a sensor on a wearable device worn by a user [0085 “…a small, wearable patch 105 with multiple bio-sensors…”], data including bodily parameter data related to the user [0087 “The system is capable in some embodiments of measuring vital signs (SpO.sub.2/hypoxia, respiration rate, heart rate, body temperature, body posture and activities, skin impedance)”]; and,
applying a model to the bodily parameter data to obtain physiological information related to the user [0105 “…biomarker is computed using signal processing and predictive model algorithms…”]; and,
deriving, from the physiological information output from the model, a physiological rank indicative of a physiological status of the user wearing the device [0062 “…calculate the Hm index…”], wherein the physiological rank is a given value on a physiological rank scale [0062-0075, these sections discuss and list the “rank” of hemodynamic response score following a pain and consciousness assessment].
Akhbardeh teaches acquiring information from a sensor, but fails to teach the sensor comprisinq an optical sensinq module includinq a plurality of lasers confiqured to emit liqht into the user's skin and a photodetector array confiqured to collect back-scattered liqht to form the bodily parameter data.
Wasson teaches the sensor comprisinq an optical sensinq module includinq a plurality of lasers [0108 “First 630a and second 630b light emitters (e.g., LEDs, lasers, etc.)…”] confiqured to emit liqht into the user's skin [0047 “Electronics 230 disposed on the flexible substrate 210 include a light detector and/or light emitter configured to detect an analyte (e.g., to measure a concentration of glucose) in a fluid within the skin…”] and a photodetector array confiqured to collect back-scattered liqht to form the bodily parameter data [0108 “…first 640a and second 640b light detectors (e.g., photodiodes, phototransistors, photoresistors, etc.) are disposed at a proximal end 621 of the sensor probe 600”, “…the light detectors 640a, 640b can detect respective responsively emitted lights…”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Akhbarden and incorporate the teachings of Wasson to include the sensor comprisinq an optical sensinq module includinq a plurality of lasers confiqured to emit liqht into the user's skin and a photodetector array confiqured to collect back-scattered liqht to form the bodily parameter data. Doing so configures the system with a configuration utilizing light emitters and photodiodes that are highly sensitive to light, allowing for precise detection of light intensity, rapid response, and lower noise compared to other systems.
Akhbardeh teaches applying a model to the bodily parameter, but fails to teach qeneratinq a delta spectrum by subtractinq baseline data from the bodily parameter data, the baseline data comprisinq an average of bodily parameter data acquired from the user over a predefined period of time.
Ma teaches qeneratinq a delta spectrum by subtractinq baseline data from the bodily parameter data [0065 “…subtract a corresponding baseline temperature difference from the temperature difference to calculate a real change in the temperature difference…”], the baseline data comprisinq an average of bodily parameter data acquired from the user over a predefined period of time [0091 “The application can calculate a linear combination (e.g., an average) of these six temperatures and store this value as a baseline temperature”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Akhbardeh and incorporate the teachings of Ma to include qeneratinq a delta spectrum by subtractinq baseline data from the bodily parameter data, the baseline data comprisinq an average of bodily parameter data acquired from the user over a predefined period of time. Doing so configures the system to “…compare the temperature of each of these regions to the baseline temperature and predict inflammation in a particular region (…) if a temperature of this particular region exceeds the baseline temperature by more than the threshold temperature difference…”, as disclosed by Ma para. 0091.
Akhbardeh teaches applying a model, but fails to teach the model is trained against bodily parameter data being associated with a clinical label derived from outputs of one or more standard point-of-care tests.
Conroy teaches [0046 “In order to train machine learning model 120, which may mean, for instance, learning the weights a.sub.1, a.sub.2, . . . , a.sub.m, in various embodiments, n paired training examples (p.sup.(1),y.sup.(1)), . . . , (p.sup.(n),y.sup.(n)) may be provided, e.g., from training database 108. p.sup.(i) may be a vector of input features for a given patient (vitals, labs, demographics, etc.) and y.sup.(i) may be a label that indicates the clinical context state of that patient”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Akhbardeh and incorporate the teachings of Conroy to include the model is trained against bodily parameter data being associated with a clinical label derived from outputs of one or more standard point-of-care tests. Doing so configures the model to have improved accuracy and enhanced pattern recognition by adjusting the model with a particular and relevant set of data.
Regarding claim 2, Akhbardeh teaches the computer-implemented method of claim 1 further comprising:
acquiring other sensor information in addition to the physiological information [Akhbardeh 0107 “The system 100 of FIG. 1 is capable of continuously measuring vital signs, critical health functions (SpO.sub.2/hypoxia, respiration rate, skin impedance, bio-potentials including ECG, heart rate, blood oxygenation, blood deoxygenation, body temperature, body posture and activities, dyspnea), and real-time objective pain (nociception)”]; and/or,
acquiring user input information [Akhbardeh 0100 “The computer may also include an input device may include any mechanism or combination of mechanisms that may permit information to be input into the computer system from, e.g., a user”].
Regarding claim 22, Akhbardeh, Wasson, Ma, and Conroy teach a wearable device [Akhbardeh 0030 “…a wearable patch device…”] comprising a processor [Akhbardeh 0009 “data processor”], the processor configured to carry out the computer-implemented method of claim 1 [see claim 1 rejection above, see also Akhbardeh 0009 “The system comprises a respiratory sensor system configured to provide measurements of respiratory metrics of said person and a data processor configured to communicate with said hemodynamic sensor system to receive said measurements of hemodynamic parameters and configured to communicate with said respiratory sensor system to receive said measurements of respiratory metrics”].
Claims 3-4 are rejected under 35 U.S.C. 103 as being unpatentable over Akhbardeh, Wasson, Ma, and Conroy as applied to claim 2 above, and further in view of Atreja (US 20200381086 A1).
Regarding claim 3, Akhbardeh, Wasson, Ma, and Conroy teach the computer-implemented method of claim 2 further comprising:
comparing the derived physiological rank with the stored physiological ranks [Akhbardeh 0048 “…
S
p
O
2
is taken out from a table stored on the memory…”].
Akhbardeh fails to teach storing a notification data table, the notification data table associating notifications with stored physiological ranks; selecting a notification to output to the user; and, outputting the selected notification to the user.
Atreja teaches storing [0072 “memory”] a notification data table [0077 “alert lookup table”], the notification data table associating notifications with stored physiological ranks [0077 “…an alert lookup table 226 comprising a plurality of alerts, each respective alert 228 in the alert data store 226 comprising one or more trigger conditions 230 and one or more actions 232”];
selecting a notification to output to the user [0109 “…a quality of life score of the subject 216 is compared on a temporal basis with each trigger condition of each alert in the alerts lookup table and, when the quality of life score of the subject on the temporal basis matches a trigger condition of the alert module 326, issues a corresponding alert”]; and,
outputting the selected notification to the user [0109 “…provide alerts to the subject 216”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Akhbardeh and incorporate the teachings of Atreja to include storing a notification data table, the notification data table associating notifications with stored physiological ranks; selecting a notification to output to the user; and, outputting the selected notification to the user. Doing so configures the system to provide a user information regarding a patient’s condition, as “Communication of such alerts to delegated medical personnel further facilitates automated remote monitoring of subjects.
Regarding claim 4, Akhbardeh, Wasson, Ma, Conroy, and Atreja teach the computer-implemented method of claim 3, wherein the notification data table further associates notification with stored other sensor information and/or stored user input information [Atreja 0139 “…the trigger condition 230 for the first alert 228 is a drop in the quality of life score by a predetermined amount over a predetermined amount of time, and the first alert 232 is a notification to the user”], and wherein the method further comprises:
comparing acquired other sensor information and/or acquired user input information with the stored other sensor information and/or the stored user input information [Atreja 0139 “…an alert module 326 compares the quality of life score of the user on a temporal basis with each trigger condition 230 of each alert 228 in the alerts lookup table 226”],
wherein the selecting the notification to output to the user is further based upon this comparison [Atreja 0139 “…when the quality of life score of the user on the temporal basis matches a trigger condition 230 of a first alert 228 in the plurality of alerts, the corresponding action 232 of the first alert 228 is fired (556)”].
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Arkbardeh in view of Wasson and Conroy.
Regarding claim 10, Akhbardeh teaches a computer-implemented method for deriving a physiological rank indicative of a physiological status of a user, the computer-implemented method comprising:
applying a model to bodily parameter data [0105 “…biomarker is computed using signal processing and predictive model algorithms…”] acquired from a sensor on a wearable device worn by a user [0085 “…a small, wearable patch 105 with multiple bio-sensors…”] to obtain physiological information related to the user [0087 “The system is capable in some embodiments of measuring vital signs (SpO.sub.2/hypoxia, respiration rate, heart rate, body temperature, body posture and activities, skin impedance)”]; and,
deriving, from the physiological information output from the model, a physiological rank indicative of a physiological status of the user wearing the wearable device [0062 “…calculate the Hm index…”], wherein the physiological rank is a value on a physiological rank scale [0062-0075, these sections discuss and list the “rank” of hemodynamic response score following a pain and consciousness assessment].
Akhbardeh teaches acquiring information from a sensor, but fails to teach the sensor comprisinq an optical sensinq module includinq a plurality of lasers confiqured to emit liqht into the user's skin and a photodetector array confiqured to collect back-scattered liqht to form the bodily parameter data.
Wasson teaches the sensor comprisinq an optical sensinq module includinq a plurality of lasers [0108 “First 630a and second 630b light emitters (e.g., LEDs, lasers, etc.)…”] confiqured to emit liqht into the user's skin [0047 “Electronics 230 disposed on the flexible substrate 210 include a light detector and/or light emitter configured to detect an analyte (e.g., to measure a concentration of glucose) in a fluid within the skin…”] and a photodetector array confiqured to collect back-scattered liqht to form the bodily parameter data [0108 “…first 640a and second 640b light detectors (e.g., photodiodes, phototransistors, photoresistors, etc.) are disposed at a proximal end 621 of the sensor probe 600”, “…the light detectors 640a, 640b can detect respective responsively emitted lights…”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Akhbarden and incorporate the teachings of Wasson to include the sensor comprisinq an optical sensinq module includinq a plurality of lasers confiqured to emit liqht into the user's skin and a photodetector array confiqured to collect back-scattered liqht to form the bodily parameter data. Doing so configures the system with a configuration utilizing light emitters and photodiodes that are highly sensitive to light, allowing for precise detection of light intensity, rapid response, and lower noise compared to other systems.
Akhbardeh teaches applying a model, but fails to teach the model is trained against bodily parameter data being associated with a clinical label derived from outputs of one or more standard point-of-care tests.
Conroy teaches [0046 “In order to train machine learning model 120, which may mean, for instance, learning the weights a.sub.1, a.sub.2, . . . , a.sub.m, in various embodiments, n paired training examples (p.sup.(1),y.sup.(1)), . . . , (p.sup.(n),y.sup.(n)) may be provided, e.g., from training database 108. p.sup.(i) may be a vector of input features for a given patient (vitals, labs, demographics, etc.) and y.sup.(i) may be a label that indicates the clinical context state of that patient”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Akhbardeh and incorporate the teachings of Conroy to include the model is trained against bodily parameter data being associated with a clinical label derived from outputs of one or more standard point-of-care tests. Doing so configures the model to have improved accuracy and enhanced pattern recognition by adjusting the model with a particular and relevant set of data.
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 JONATHAN M HANEY whose telephone number is (571)272-0985. The examiner can normally be reached Monday through Friday, 0730-1630 ET.
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/JONATHAN M HANEY/Examiner, Art Unit 3791
/JUSTIN XU/Primary Examiner, Art Unit 3791