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 .
DETAILED ACTION
This action is in reference to the communication filed on 11 SEPT 2026.
Amendments to claims 1-4, 13-16 are entered and considered, as is the cancellation of claims 5, 6, 17, 18, and previous withdrawal of claims 9-12.
Claims 1-4, 7, 8, 13-16, 19, 20 are present and examined.
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, 7, 8, 13-16, 19, 20 rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. As explained below, the claim(s) are directed to an abstract idea without significantly more.
Step One: Is the Claim directed to a process, machine, manufacture or composition of matter? YES
With respect to claim(s) 1-4, 7, 8, 13-16, 19, 20 the independent claim(s) 1, 13 each recite a method and a device, each of which are a statutory category of invention.
Step 2A – Prong One: Is the claim directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea? YES
With respect to claim(s) 1-4, 7, 8, 13-16, 19, 20, the independent claim(s) (claims 1, 13) is/are directed, in part, to:
Claim 1: A method
obtaining an actual event related to medical data of a patient
generating a virtual event by predicting a next state of the patient and a reward when a predetermined action is performed on the actual event, the virtual event being different from the actual event and being generated based on one or more features selected from the actual event;
determining a probability of the virtual event occurring, based on the medical data, by using a virtual event probability model ;
based on the actual event, the virtual event, and the probability of the virtual event, action value for the reward of an action that is performed in a current state of the patient and
determining and outputting a medical action to treat the patient based on the current state of the patient,
in a case of the actual event, updating the model by using a general Bellman equation and determined a predicted value of the reward as the state-action value; and
in a case of the virtual event, updating the model by using an optimized Bellman equation into which the probability of the virtual event is incorporated, such that, as the probability of the virtual event increases, the state-action value is determined so that the reward predicted for the virtual event is minimized.
These claim elements are considered to be abstract ideas because they are directed mental processes – i.e. concepts performed in the human mind including observation, evaluation, judgment and opinion. Obtaining data is an observation, while determining probability and/or a medical action based on the values obtained are examples of evaluation, judgement and/or opinion, in that they could be performed in the mind.
Examiner also notes that the claims have been amended to recite training the model itself using a general and/or optimized Bellman equation. This represents the creation of specific mathematical interrelationships between data. As such the training of the machine learning model represents a mathematical concept that is interpreted to be a part of the identified abstract idea(s), supra. The types of identified abstract idea(s) are considered together as a single abstract idea for analysis purpose(s).
If a claim limitation, under its broadest reasonable interpretation, covers concepts performed in the human mind, then it falls within the “mental processes” categories of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A – Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application? NO.
This judicial exception is not integrated into a practical application. In particular, the claim(s) recite(s) additional elements: Claim 1 recites an “electronic device” understood to be analogous to a computer, while claim 13 recites “an electronic device comprising a processor” to perform the claim steps. Claims 1, 13 have also been also include a “database” from which information is retrieved, and the training and actual application of the trained model. The electronic device(s) and processor, as well as the database itself are recited at a high-level of generality and as such amount to no more than adding the words “apply it” to the judicial exception, or mere instructions to implement the abstract idea on a computer, or merely uses the computer as a tool to perform the abstract idea (see MPEP 2106.05f), or generally links the use of the judicial exception to a particular technological field of use/computing environment (see MPEP 2106.05h). Examiner finds similarly with regard to the training/application of the trained model – the training does not improve the model itself nor any technical aspects therein. Examiner finds no improvement to the functioning of the computer, the database or any other technology or technical field in the electronic devices/processor/training as claimed (see MPEP 2106.05a), nor any other application or use of the judicial exception in some meaningful way beyond a general like between the use of the judicial exception to a particular technological environment (see MPEP 2106.05e). Further, the storage and retrieval of data is generally found to be analogous to adding insignificant extra solution activity to the judicial exception(s) identified (see MPEP 2106.05g).
Accordingly, this/these additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? NO.
The independent claim(s) is/are additionally directed to claim elements such as: Claim 1 recites an “electronic device” understood to be analogous to a computer, while claim 13 recites “an electronic device comprising a processor” to perform the claim steps. Claims 1, 13 include a “database” from which information is retrieved, and the training and actual application of the trained model. When considered individually, the above identified claim elements only contribute generic recitations of technical elements to the claims. It is readily apparent, for example, that the claim is not directed to any specific improvements of these elements. Examiner looks to Applicant’s specification in:
[0012] The training of the model may include training the model to determine the state value by using a Bellman equation, which considers the probability of the virtual event.
[0056] In the reinforcement learning, an optimal policy may be a policy, among one or more policies, for obtaining maximum rewards when the agent 110 interacts with the environment 120 in the environment 120 given. To calculate a predicted value for the reward in the reinforcement learning, a Bellman equation may be used as shown in Equation 1 below.
[0131] The components described in the embodiments may be implemented by hardware components including, for example, at least one digital signal processor (DSP), a processor, a controller, an application-specific integrated circuit (ASIC), a programmable logic element, such as a field programmable gate array (FPGA), other electronic devices, or combinations thereof. At least some of the functions or the processes described in the embodiments may be implemented by software, and the software may be recorded on a recording medium. The components, the functions, and the processes described in the embodiments may be implemented by a combination of hardware and software.
[0132] The embodiments described herein may be implemented using a hardware component, a software component, and/or a combination thereof. A processing device may be implemented using one or more general-purpose or special-purpose computers, such as, for example, a processor, a controller and an arithmetic logic unit (ALU), a DSP, a microcomputer, an FPGA, a programmable logic unit (PLU), a microprocessor, or any other device capable of responding to and executing instructions in a defined manner. The processing device may run an operating system (OS) and one or more software applications that run on the OS. The processing device also may access, store, manipulate, process, and generate data in response to execution of the software. For purpose of simplicity, the description of a processing device is singular; however, one of ordinary skill in the art will appreciate that a processing device may include a plurality of processing elements and a plurality of types of processing elements. For example, the processing device may include a plurality of processors, or a single processor and a single controller. In addition, different processing configurations are possible, such as parallel processors.
These passages, as well as others, makes it clear that the invention is not directed to a technical improvement. When the claims are considered individually and as a whole, the additional elements noted above, appear to merely apply the abstract concept to a technical environment in a very general sense. The most significant elements of the claims, that is the elements that really outline the inventive elements of the claims, are set forth in the elements identified as an abstract idea. The fact that the generic computing devices are facilitating the abstract concept is not enough to confer statutory subject matter eligibility.
As per dependent claims 2-4, 7, 8, 14-16, 19, 20:
Dependent claims 2-4, 7, 8, 14-16, 19-20 are not directed any additional abstract ideas and are also not directed to any additional non-abstract claim elements. Rather, these claims offer further descriptive limitations of elements found in the independent claims and addressed above – such as the training of the model, as well as additional information regarding the types of events and the probabilities therein. While these descriptive elements may provide further helpful context for the claimed invention these elements do not serve to confer subject matter eligibility to the invention since their individual and combined significance is still not heavier than the abstract concepts at the core of the claimed invention.
Prior Art
Claims 1-4, 7, 8, 13-16, 19, 20 are believed to be free of the prior art
The closest prior art of record is believed to be:
Buchard et al (US 20210327578)
Dalli et al (US 20220147876)
Wang et al (20200373017)
Kim et al (US 20240221940)
Buchard teaches using actual events to predict a next state of a patient represented as a “virtual” or predicted event, and using that information to predict a benefit to a patient based on an action taken in response to the predicted event – i.e. the benefit of a triage or a treatment to a patient based on a predicted event/condition. Medical data is used to determine the probability of the predicted event occurring, and then the actual original event and the predicted probability of the virtual event, a model is trained to determine the reward or benefit to a current patient based on their current state, and an action or intervention is performed. Buchard also teaches the use of a Bellman equation in Q-L learning.
Dalli teaches a similar means of predicting a current/future state of an agent, specifically Double-Q deep learning, and specifically teaches two neural networks to perform a Bellman iteration, one for a prediction and one for the target/goal/reward accomplished by the prediction. Dalli teaches that such a prediction means has applicability in both virtual and medical settings.
Wang also teaches a reinforcement learning process as applied to clinical pathways such as diagnoses and future pathways. This prediction is used to allow professionals to make decisions about appropriate treatment(s) and/or other interventions. This collected information is also used to optimize the treatment(s) available to a patient including specific treatment timelines and/or professionals to be involved, as well as referencing policy and cost considerations.
Kim teaches a means of optimizing a treatment path using reinforcement learning for similar episodes in the past. In particular Kim teaches the use of an optimized and a general Bellman equation at the same time to create a predictive model, and using a virtual episode to predict future or subsequent states.
However, Examiner finds Applicant’s amendments and remarks as filed on 11 SEPT 2026 to be persuasive. The combination of references does not teach the amended generation of the virtual event, nor the relationship between the actual and virtual events as considered in terms of a probability. Examiner also agrees that the cited references, while teaching or inferring different Bellman Equation processing, do not specifically teach updating the model itself with different iterations of the Bellman Equation processing based on event being actual or virtual, and if virtual, based on a probability as currently claimed.
The Examiner hereby asserts that the totality of the evidence neither anticipates nor renders obvious the particular combination of elements as claimed. That is, the Examiner emphasizes the claims as a whole and hereby asserts that the totality of the evidence fails to set forth, either explicitly or implicitly, an appropriate rationale for combining or otherwise modifying the available prior art to arrive at the claimed invention. The combination of features as claimed would not be obvious to one of ordinary skill in the art because any combination of the evidence at hand to reach the combination of features as claimed would require a substantial reconstruction of Applicant’s claimed invention relying on improper hindsight bias.
Response to Arguments
Applicant’s remarks as filed on 11 SEPT 2026 have been noted.
Applicant’s remarks regarding the 101 rejection begin on page 8 with a recitation of exemplary claim 1. Examiner respectfully disagrees with Applicant’s conclusion that the claims do not recite a mental process. Examiner also notes that the rejection above has been updated to include mathematical concepts in the specific addition of at least the general Bellman equation.
Examiner finds Applicant’s remarks regarding a practical application to also be unpersuasive on page 9. The bellman equation itself is more appropriately analyzed at the first step of the analysis. Examiner notes as discussed above the claims instead appear to be applying the additional elements to the abstract idea(s). Training a model does not inherently result in eligible subject matter.
On page 10, Applicant turns to a discussion of step 2b. Examiner respectfully notes that again much of what is discussed is more appropriately categorized as part of the abstract idea(s) identified above. Applicant does not clarify what exactly is believed to be significantly more, and Examiner respectfully submits that well understood is not the sole test to support a finding of significantly more.
Applicant discusses the prior art beginning on page 10; Examiner notes that the amendments and remarks have been found to be persuasive as noted above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KATHERINE KOLOSOWSKI-GAGER whose telephone number is (571)270-5920. The examiner can normally be reached Monday - Friday.
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/KATHERINE . KOLOSOWSKI-GAGER/
Primary Examiner
Art Unit 3687
/KATHERINE KOLOSOWSKI-GAGER/Primary Examiner, Art Unit 3687
