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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 01/08/2026 has been entered.
Response to Amendment
This Office Action is responsive to the amendment filed on 01/08/2026. As directed by the amendment: Claims 1, 7, and 15 have been amended, claim 20 have been cancelled, and claim 21 has been added. Thus, claims 1-19 and 21 are presently under consideration in this application.
Response to Arguments
Applicant's arguments, see pages 13-24, filed 01/08/2026, regarding 35 U.S.C. 101 have been fully considered but they are not persuasive.
Applicant cites specific limitation on pages 13-14 to assert that the claim is not directed to a mental process, and argues on page 14 that similar to SRI Int’l Inc, the claims cannot be performed in the mind. Specifically, Applicant argues that “the claimed steps identified above cannot practically be performed in the human mind because the claims require two independent machine learning algorithms to work in tandem to generate and validate a sepsis alert and calculate time zero. See as-filed application, para. [0062]. By way of example, the first machine learning algorithm generates a preliminary alert for sepsis, and the second machine learning algorithm independently validates the output of the first machine learning algorithm by identifying indications of severe sepsis and calculating time zero to reduce false positives and negatives within the first machine learning algorithm. See as-filed application, para. [0077]. Notably, these two algorithms "more accurately identify the indications of sepsis and measure and determine the earliest period of time zero." See as-filed application, para. [0077]. Such coordinated algorithmic operations cannot be practically performed mentally or with pen and paper.” Applicant also argues on page 15 that “The claims require automatically validating a sepsis alert from a first machine learning algorithm using a second, independent machine learning algorithm, while simultaneously updating a GUI based on additional data. This involves continuous, real-time collection, calculation, and assessment of multiple patient conditions including at least abnormal glucose levels, abnormal white blood cell counts, abnormal platelet counts, abnormal pO2 levels, and other clinical criteria, to determine whether thresholds are met, all while simultaneously updating a graphical user interface to reflect the current status. A human mind is simply not capable of performing such continuous, simultaneous, real-time operations that require instantaneous processing of streaming patient data, concurrent execution of two independent machine learning algorithms, and simultaneous updating of a graphical user interface.”
Examiner disagrees because the use of machine learning algorithms is by definition automating the human thinking process with a computer. A human and/or doctor could analyze 3 conditions and determine if elements meet a threshold to calculate a time zero. Specifically, [0009] of the instant specification discloses that the onset of sepsis and the time zero can be manually calculated by a medical provider.
Applicant then asserts on page 16 that
the pending claims recite a system that automatically stores, compiles, calculates, validates, and generates sepsis alerts more quickly and accurately than conventional techniques, thereby improving early diagnosis and reducing mortality from sepsis as compared to prior systems. See As-filed Application, para. [0079]. These are not merely abstract concepts applied using generic computer components but are instead specific technological improvements that enhance the speed, accuracy, and reliability of sepsis detection systems.
Examiner disagrees because "claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures | LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015).
Spanning pages 16-18, Applicant provides three examples of claim limitations that Applicant believes recite technical improvements of sepsis detection systems, and that are similar to those of Cardionet, LLC v. InfoBionic, Inc. and as addressed in MPEP 2106.04(d)(I). First, Applicant specifically argues that the claimed dual-algorithm architecture is a specific technical solution of reducing false positives and false negatives and represents a technical improvement to sepsis detection technology. Second, Applicant points to real-time simultaneous that is specific technical implementation in which the system dynamically recalculates time zero as new patient data arrives and simultaneously updates the graphical user interface to reflect the recalculated values in real time, as a specific technical improvement. Finally, applicant points to automated data aggregation is a technical improvement as it addresses the fragmentation of patient data. Applicant argues that these technical mechanisms are analogous in CardioNet, LLC v. InfoBionic, Inc. because both are directed to improved medical monitoring systems.
Examiner disagrees because the abstract idea cannot be an improvement, as the Applicant is asserting. MPEP 2106.05(a): It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below. In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception. See MPEP § 2106.04(d) (discussing Finjan, Inc. v. Blue Coat Sys., Inc., 879 F.3d 1299, 1303-04, 125 USPQ2d 1282, 1285-87 (Fed. Cir. 2018)). Thus, it is important for examiners to analyze the claim as a whole when determining whether the claim provides an improvement to the functioning of computers or an improvement to other technology or technical field.
Applicant is asserting the abstract idea itself as the improvement. However, the abstract idea cannot be an “additional element” that shows integration into a practical application. The order of calculations and the particular calculations, including the use of the dual algorithm architecture and simultaneous time zero calculation in real-time, claimed do not make the abstract idea any less abstract. The claims are currently structured as simply using a generic computer to implement the abstract idea (mental process), which is not enough to show a practical application. Furthermore, the aggregating of data is an additional element of data transferring, amounting to extra-solution activity
Examiner further disagrees because CardioNet, LLC v. InfoBionic, Inc. was directed to an improper assertion that the claimed device contained conventional structure. In the instant case, there is no conventional structure that is asserted as there is no structure similar to Cardionet that is claimed. Therefore, any argument relating Cardionet to not being an abstract idea is deemed moot. Furthermore, the instant claims are directed to a different field of endeavor than Cardionet.
Applicant further argues on page 19 that
the USPTO determined that a claim involving automated identification of newly added medical record data, conversion of the data into a standardized format, and real-time transmission of updated patient information to remote users constituted a practical application because it improved the functioning of the electronic medical record system by enabling standardized, real-time information sharing. Unlike the ineligible claim in Example 42, which merely stored and provided access to medical records without real-time processing or transmission, the pending claims actively process incoming data through dual machine learning algorithms and simultaneously update both the calculated time zero and the GUI in real time. Likewise, the pending claims are directed to a specific technical implementation that aggregates patient data from multiple enterprise health information systems, processes that data through two independently operating machine learning algorithms, and communicates updated sepsis alerts and recalculated time-zero determinations to healthcare providers in real time via a dynamically updated graphical user interface. As in the eligible claim of Example 42, the claimed system integrates the underlying abstract ideas into a concrete medical-technology architecture that improves real-time clinical decision-making and system functionality.
Examiner disagrees because the claims are directed to different subject matter as example 42 requires the converting of non-standardized data, which the instant claims do not so. The instant claims are directed displaying different data points by implementing the Abstract idea on a computer.
Applicant then argues on page 20 that
the claims are directed to an improvement in technology, which supports a finding of "significantly more" under Step 2B of the Alice inquiry. See, e.g., November Memo, pp. 2-3, discussing indications that a claim is directed to an improvement in computer-related technology, which render a claim eligible for patent protection; see also MPEP 2106.05(a).
Examiner disagrees as the November memo is directed to the improvement of storage using machine learning, whereas the instant claims are directed to the using machine learning to process data faster/more efficiently, which is simply automating the human mind.
Applicant then argues on page 20 that
Second, the ordered combination of claim elements is not well-understood, routine, or conventional. Even if individual elements of the claims were known in the prior art, the specific combination recited in the claims ((i) generating a sepsis alert via a first machine learning algorithm, (ii) validating that alert using a second, independent machine learning algorithm including a predictive model, (iii) calculating time zero based on the concurrence of three conditions within a predetermined period, (iv) compiling a patient-specific sepsis bundle in real time, (v) generating a GUI with countdown timers and status indicators, and (vi) simultaneously updating both the time zero calculation and the GUI responsive to additional aggregated data) represents an unconventional technical arrangement that is not routine in the field of sepsis monitoring. The specification confirms that prior systems did not provide this combination of features. See As-filed Specification, para. [0011] ("No solutions in the current state of the art include a collection of real time monitored data that demonstrates all available sepsis data within the data repository simultaneously. Thus, no solutions include an automated sepsis time zero or a dashboard that quickly summarizes data from a variety of sources to determine a strategy for compliance with bundles such as a SEP-1 bundle."). This is not a case where generic computer components are merely used to perform an abstract idea faster; rather, the claims recite a specific technical architecture that did not exist in the prior art.
Examiner disagrees since the processing of data on a microcontroller unit is merely performing this process on a generic computer structure. The transmitting of signals is simply a generic computer function performed by a generic computer structure, wherein implementing the abstract idea with a generic computer is not enough to show integration into a practical application or significantly more than the abstract idea itself. The transmission of data to and from the sensor systems is merely data gathering, which is insignificant extra-solution activity.
Applicant then argues on pages 20-21 that
the absence of any prior art rejections further confirms that the claims are
directed to a specific, non-conventional approach. See Office Action, p. 5. While novelty and non-
obviousness are distinct from the Step 2B inquiry, the absence of prior art rejections supports that
the claimed combination is not conventional. The Office's own prior art search did not identify
any teaching of using dual, independent machine learning algorithms to generate and validate sepsis alerts in real time, which strongly supports that this approach is not routine or conventional.
As MPEP 2106.05(d) explains, just because a claim element appears in the prior art does not make
it "well-understood, routine, and conventional" for purposes of Step 2B. Here, the Examiner has
identified no prior art teaching the claimed combination, further supporting that the claims recite
an inventive concept.
Finally, the claims do not attempt to preempt all ways of performing the alleged abstract
idea, which also further supports a finding of "significantly more" under Step 2B (see, e.g.,
November Memo, pp. 3-4). In particular, the claims recite a specific technical implementation
involving two independent machine learning algorithms, real-time data aggregation, and
simultaneous GUI updates, not a broad preemption of all sepsis detection methods.
As made clear by the courts, the "‘novelty’ of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the § 101 categories of possibly patentable subject matter." Intellectual Ventures | v. Symantec Corp., 838 F.3d 1307, 1315, 120 USPQ2d 1353, 1358 (Fed. Cir. 2016) (quoting Diamond v. Diehr, 450 U.S. at 188-89, 209 USPQ at 9). Furthermore, Examiner disagrees as the November memo is directed to the improvement of storage using machine learning, whereas the instant claims are directed to the using machine learning to process data faster/more efficiently, which is simply automating the human mind.
Applicant argues on page 21-22 that
claim 21 requires that the server is configured to modify the first status indicator corresponding to the first sepsis bundle compliance step such that the first status indicator corresponds to the first sepsis bundle compliance step reflects completion of the first sepsis bundle compliance step for the patient. This limitation involves modifying a first status indicator within a graphical user interface, which cannot be performed mentally. A human mind cannot modify a GUI.
Examiner agrees, however, independent claim 1 still contains the mental process, and such an argument is not made by the Examiner.
Applicant then argues on pages 22-23 that
This is not merely an abstract concept. It recites a concrete, technological operation that directly affects the functioning of the sepsis-monitoring system by causing the GUI to automatically update in real time based on new clinical information, providing clinicians with real-time visual feedback regarding bundle compliance status. Similar to the automated mold-operation steps in Diehr, this GUI-modification step imposes a technological constraint and transforms any alleged abstract idea into a specific, practical implementation.
Moreover, this is not merely "displaying data" or a form of insignificant post-solution activity. Instead, claim 21 requires a specific technical sequence: (1) receiving additional data indicating completion of a compliance step; (2) processing that data to determine that a particular bundle step has been completed; and (3) dynamically modifying a designated GUI status indicator to reflect that completion for a specific patient. These operations create a closed-loop, real-time feedback mechanism in which the GUI is not a passive output but an active component continuously synchronized with incoming clinical data.
By requiring the system to automatically update a specific GUI element in response to newly received completion data, the claim tightly integrates any alleged abstract idea into a concrete technological system designed to improve sepsis-bundle compliance workflows. This constitutes a meaningful limitation under MPEP § 2106.05(e), just as the mold-operation steps did in Diehr.
Examiner disagrees because the generic hardware component, the server, transfers and selecting data, that ends up displayed to a medical provider, which are all additional elements that do not integrate the judicial exception into practical application. The abstract idea cannot be an “additional element” that shows integration into a practical application. The order of calculations and the particular calculations claimed do not make the abstract idea any less abstract. The claims are currently structured as simply using a generic computer to implement the abstract idea (mental process), which is not enough to show a practical application. Furthermore, the aggregating of data is an additional element of data transferring, amounting to extra-solution activity.
Lastly, Applicant argues on pages 23-24 that
claim 21 is directed to an improvement in technology, which supports a finding of "significantly more" under Step 2B of the Alice inquiry (see, e.g., November Memo, pp. 2-3). Furthermore, claim 21 does not preempt all ways of performing the alleged abstract idea, as the claim is directed to a specific implementation, e.g., modifying a status indicator within a GUI to reflect completion of a sepsis bundle compliance step, rather than a broad preemption of all methods for tracking clinical compliance. (see, e.g., November Memo, pp. 3-4). This is further supported via the lack of any pending prior art rejections (e.g., claim 21 is patentable, at least due to its respective dependency from claim 1).
Examiner disagrees as the November memo is directed to the improvement of storage using machine learning, whereas the instant claims are directed to the using machine learning to process data faster/more efficiently, which is simply automating the human mind.
Therefore, the rejection 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 1-19 and 21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Each of independent claims 1, 7, and 15 recites a step automatically calculate, based on the plurality of data and the second machine learning algorithm, a time zero in real time for the patient, which is a mental process. This judicial exception is not integrated into a practical application because the generically recited computer elements (ie. a storage device, a processing circuitry, implantable medical device), determining values, and calculating a time zero do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations are to receiving data, processing data, and calculating a time zero, which are all well-understood, routine, and conventional computer functions. See MPEP § 2106.05(d).
MPEP 2106(III) outlines steps for determining whether a claim is directed to statutory subject
matter. The stepwise analysis for the instant claim is provided here.
Step 1 – Statutory categories
Claim 1 and 15 is directed to a system (i.e. machine) and thus meets the step 1 requirements.
Claim 7 is directed to a method and thus meets the step 1 requirements.
Step 2A – Prong 1 – Judicial exception (j.e.)
Regarding claims 1, 7, and 15, the following step is an abstract idea:
“automatically calculate, based on the plurality of data and the second machine learning algorithm, a time zero in real time for the patient”, which is a mental process when given its broadest reasonable interpretation. As discussed in MPEP 2106.04(a)(2)(II), the mental process grouping includes observations, evaluations, judgements, and opinions. In this case, a human and/or doctor could analyze 3 conditions and determine if elements meet a threshold to calculate a time zero. Specifically, [0009] of the instant specification discloses that the onset of sepsis and the time zero can be manually calculated by a medical provider.
Step 2A – Prong 2 – additional elements to integrate j.e. into a practical application
Regarding claims 1, 7, and 15, the abstract idea is not integrated into a practical application.
The following claim elements do not add any meaningful limitation to the abstract idea:
- “data repository”, “a computer network”, “server”, “processor”, “memory”, “plurality of communications”, and “a server hardware computing device” are recited at a high level of generality amounting to generic computer components for implementing abstract idea [MPEP 2106.05(b)];
It is noted that the first and second machine learning model algorithm and the predictive model are by definition automating the human thinking process with a computer.
- “(updated) time zero”, “plurality of data”, “documentation data”, “clinical data”, “sepsis alert”, “conditions”, “documentation data input”, “elements”, “first and second list”, “first and second thresholds”, “GUI”, “first and second countdown”, “sepsis bundle compliance steps”, “first and second status indicators”, “additional data”, first sepsis bundle compliance step”, “reassessment compliance step/plurality of sepsis recovery compliance steps”, and “probability score” are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)];
- “indication of sepsis”, “a patient's mental metal status, an abnormal glucose, an abnormal white blood cell count, an elevated heart rate, an abnormal respiratory rate, and abnormal body temperature”, and “an abnormal platelet count, an abnormal p02, an abnormal Bilirubin, an abnormal creatinine level, an abnormal lactate level, an abnormal partial thromboplastin time (PTT)/prothrombin time (PT), and an abnormal international normalized ratio (INR) level” are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)].
Step 2B – significantly more/inventive concept
The following claim elements do not add any meaningful limitation to the abstract idea:
- “data repository”, “a computer network”, “server”, “processor”, “memory”, “plurality of communications”, and “a server hardware computing device” are recited at a high level of generality amounting to generic computer components for implementing abstract idea [MPEP 2106.05(b)];
It is noted that the first and second machine learning model algorithm and the predictive model are by definition automating the human thinking process with a computer.
- “(updated) time zero”, “plurality of data”, “documentation data”, “clinical data”, “sepsis alert”, “conditions”, “documentation data input”, “elements”, “first and second list”, “first and second thresholds”, “GUI”, “first and second countdown”, “sepsis bundle compliance steps”, “first and second status indicators”, “additional data”, first sepsis bundle compliance step”, “reassessment compliance step/plurality of sepsis recovery compliance steps”, and “probability score” are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)];
- “indication of sepsis”, “a patient's mental metal status, an abnormal glucose, an abnormal white blood cell count, an elevated heart rate, an abnormal respiratory rate, and abnormal body temperature”, and “an abnormal platelet count, an abnormal p02, an abnormal Bilirubin, an abnormal creatinine level, an abnormal lactate level, an abnormal partial thromboplastin time (PTT)/prothrombin time (PT), and an abnormal international normalized ratio (INR) level” are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)].
The additional elements of claims 1, 7, and 15, when considered separately and in combination, do not add significantly more (ie. an inventive concept) to the abstract idea. As discussed above with respect to the integration of the abstract idea into a practical application, data repository, computer network, server, processor, memory, and server hardware computing device, along with their associated functions, are recited at a high level of generality and simply amount to implementing the abstract idea on a computer.
Dependent claims 2-6, 8-14, 16-19, and 21 do not integrate the abstract idea into a practical application and do not add significantly more to the abstract idea of claims 1, 7, and 15. The dependent claim limitations are directed to the GUI [display data] (claims 2-5, 10-12, 14, 16-18, and 21), an indicator [extra-solution activity] (claims 6 and 19), predictive model [implementing data processing on a processor] (claim 8), identifying sepsis [extra-solution activity] (claim 9), and recovery time [extra-solution activity] (claim 13).
In summary, claims 1-19 and 21 are directed to an abstract idea without significantly more and, therefore, are patent ineligible.
Conclusion
Claims 1-19 and 21 overcome the prior art but are still rejected under 35 U.S.C. 101.
The following is a statement of reasons for the indication of the claims overcoming the prior art:
The automatic calculating and updating time zero in real time based on 3 conditions of documentation data input, two elements meeting a first threshold, and two elements meeting a second threshold, and compiling a plurality of sepsis bundle compliance steps in real time, and using a GUI for alerts, and first and second countdowns for completing sepsis bundle compliance steps and reassessment compliance step and updating the GUI to reflect the additional data by modifying the first status indicator in response to additional data indicated completed first sepsis bundle compliance step are not conventionally relied upon in determining early detection of sepsis and are therefore allowable over the prior art.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOUSSA M HADDAD whose telephone number is (571)272-6341. The examiner can normally be reached M-TH 8:00-6:00.
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/MOUSSA HADDAD/ Examiner, Art Unit 3796
/Jennifer Pitrak McDonald/ Supervisory Patent Examiner, Art Unit 3796