DETAILED ACTION
Status of Claims
This action is in reply to the communication filed on 14 November, 2025.
Claims 1, 3, 6, 7, 10, 11 and 13 have been amended.
Claim 5 has been cancelled.
Claims 1, 3, 4 and 6 – 14 are currently pending and have been examined.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 14 November, 2025 has been entered.
Claim Interpretation
The claims recite a process, performed by a processing apparatus, for determining a combination of trained models that satisfies a condition according to acquired patient and environment information. The specification discloses that the apparatus selects a combination of trained models (one model for each processing step) having a speed and/or an accuracy that satisfy the needs of a user, and performs processing on acquired target data, such as a medical image, using the selected trained models. (See the published specification (2023/0326564 A1) @ 0018) Here, the needs of the user are indicated by pressing a button on a user interface for prioritizing either speed or accuracy.
Patient information includes: a patient ID, name, gender, age, past medical history, lifestyle, habit, electronic medical records, such as findings, disease names, vital signs, etc. (@ 0020). Patient information may also include an indication of urgency or of an emergency (@ 0039) Environmental information includes information related to the system environment for executing analytical processing using a trained model, or information related to the scale of the hospital. The system environment includes information such as the number of workstations executing the models, the workstation CPU, and memory specifications. The scale of the hospital includes type of facility, number of staff, department types. Target information includes a medical image or time-series vital sign data. (@ 0038)
The apparatus includes a calculation function for calculating processing time (i.e. speed) and estimation of accuracy for the trained models, using some unspecified calculation, and which are stored in association with each other. Speed and accuracy for each model may be ranked as “Excellent”, “Good”, “Average”, and “Poor”. (@ 0028, 0041, 0046, 0063) The specification recognizes that speed and accuracy are opposing characteristics of trained models: faster is less accurate, in general. (0003) Whether to prioritize speed or accuracy is determined based on a user’s instructions or preference, including a selection made on a user interface; or based on the presence of data indicating whether speed or accuracy should be prioritized. For example, speed should be prioritized if it can be determined from the patient information that the case is an emergency; and accuracy should be prioritized if supplemental information indicates that the findings from the model will be used for reference. (@ 0039, 0048)
As such, Examiner construes that the recited “condition” is a speed requirement or an accuracy requirement. Therefore, when the requirement is for speed is selected by the user, the apparatus selects a model having a high calculated speed; and when the requirement selected by the user is for accuracy, the apparatus selects a model with high accuracy.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1, 3, 4 and 6 – 14 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. Claims 1, 10 and 11 recite: “determining a combination of trained models that satisfies a condition according to patient information and the environment information”. The claims further recite: “determine the combination of trained models based on an action of pressing, by the user, the speed-prioritized button or the accuracy-prioritized button.” Examiner cannot determine the metes and bounds of the claims. In particular, it is unclear how the combination of models is determined. For example, an algorithm may determine the combination of models that meet a condition according to target patient and environmental information; however, a user may override any determined combination by manual selection. A user may make a selection based on user preference alone, and not based on satisfying a condition according to patient or environmental information. Appropriate correction or clarification is required.
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.
The following rejection is formatted in accordance with MPEP 2106.
Claim 10 is representative. Claim 10 recites:
A medical information processing method, comprising:
acquiring patient information relating to a target patient, environment information relating to an environment for execution, and target data relating to the target patient, the environment information including at least one of a system environment for executing a trained model or a scale of a hospital;
determining, from a plurality of trained models differing from each other in processing speed and accuracy, a combination of trained models that satisfies a condition according to the patient information and the environment information; and
displaying a speed-prioritized button and an accuracy-prioritized button;
wherein the plurality of trained models are prepared for each of one or more analytical processing steps, and
when a task that includes a plurality of analytical processing steps is to be performed, the method further comprises determining one trained model from the prepared plurality of trained models for each analytical processing step to determine the combination of trained models based on an action of pressing, by a user, the speed-prioritized button or the accuracy-prioritized button; and
displaying information relating to a current analytical processing step indicating a real time progress of the combination of trained models.
Claim 11 recites medium with instructions executed by a processor, and Claim 1 recites an apparatus that executes the steps of the method recited in Claim 10.
Claims 1, 3, 4 and 6 – 14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. a law of nature, a natural phenomenon, or an abstract idea), and does not include additional elements that either: 1) integrate the abstract idea into a practical application, or 2) that provide an inventive concept – i.e. element that amount to significantly more than the abstract idea. The Claims are directed to an abstract idea because, when considered as a whole, the plain focus of the claims is on an abstract idea.
STEP 1
The claims are directed to an apparatus, a method and non-transitory computer readable medium which are included in the statutory categories of invention.
STEP 2A PRONG ONE
The claims, as illustrated by Claim 10, recite limitations that encompass an abstract idea including:
acquiring patient information relating to a target patient, environment information relating to an environment for execution, and target data relating to the target patient, the environment information including at least one of a system environment for executing a trained model or a scale of a hospital;
determining, from a plurality of trained models differing from each other in processing speed and accuracy, a combination of trained models that satisfies a condition according to the patient information and the environment information, wherein the plurality of trained models are prepared for each of one or more analytical processing steps, and
when a task that includes a plurality of analytical processing steps is to be performed, determining one trained model from the prepared plurality of trained models for each analytical processing step to determine the combination of trained models based on an action of pressing, by a user, the speed-prioritized button or the accuracy-prioritized button.
The claims, as illustrated by Claim 10, recite limitations that encompass an abstract idea within the “mental processes” grouping – concepts performed in the human mind including observation, evaluation, judgment and opinion. The claims require acquiring information (i.e. collecting), determining a condition according to the information (i.e. analyzing), determining a combination of models, each having a different speed and accuracy, that satisfies the condition (i.e. comparing) and selecting one trained model for each of one or more analytical processing steps.
Collecting and analyzing data and displaying the results is abstract, when performed using conventional computer and network technology, whose implicit exclusion from U.S.C. 101 undergirds the information-based category of abstract ideas. Similarly, selecting information, by content or source, for collection, analysis and display is an ordinary mental process. (Electric Power Group v. Alstom S.A. (Fed Cir, 2015-1778, 8/1/2016)). (SEE MPEP 2106.04(a)(2) III)
The specification discloses that the condition is either processing speed or accuracy; and that the processing speed and accuracy for each model is calculated in advance, and stored in a memory. The specification discloses that information is acquired from an electronic medical records system, image server or memory, at a high level of generality. Analyzing patient information to determine a condition, such as whether processing speed or accuracy should be prioritized, and selecting a model that has a matching speed or accuracy, is a process that, except for generic computer implementation steps, can be performed in the human mind. For example, if the condition is “high accuracy”, the pre-determined accuracy of the models is compared to find those models that have “high accuracy” (i.e. “Excellent” or “Good”). Comparing a model’s calculated accuracy to an accuracy set as a condition for the model, and selecting the appropriate model, is a process that can be performed in the human mind. In any event, a user selecting whether to prioritize speed or accuracy by pressing a button on a graphical user interface is an ordinary mental process. As such, the claims recite an abstract idea within the mental process grouping.
The claims, as illustrated by Claim 10, recite limitations that encompass an abstract idea within the “certain methods of organizing human activity” grouping –
managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions.
The claims recite determining and selecting a combination of models that satisfy a condition. This is akin to the “filtering” in BASCOM. That is, the claims filter a combination of models for use from a plurality of models, based on the model matching a condition. As such, the claims recite an abstract idea within the certain methods of organizing human activity grouping.
STEP 2A PRONG TWO
The claims recite limitations that include additional elements beyond those that encompass the abstract idea above including:
displaying a speed-prioritized button and an accuracy-prioritized button; and determine the combination of trained models based on an action of pressing, by a user, the speed-prioritized button or the accuracy-prioritized button;
displaying information relating to a current analytical processing step indicating a real time progress of the combination of trained models.
A medical information processing apparatus comprising processing circuitry
A non-transitory computer-readable medium having recorded thereon a plurality of computer-executable instructions.
However, these additional elements do not integrate the abstract idea into a practical application of that idea in accordance with the MPEP. (see MPEP 2106.05)
The processing apparatus and medium are recited at a high level of generality such that it amounts to no more than instructions to apply the abstract idea using a generic computer component. Similarly, “buttons” displayed on a user interface for manual user selection of speed-prioritized or accuracy-prioritized models are generic computer components. These elements merely add instructions to implement the abstract idea on a computer, and generally link the abstract idea to a particular technological environment.
Similarly, “buttons” displayed on a user interface for manual user selection of speed-prioritized or accuracy-prioritized models are generic computer components. The recited displaying is performed on a generic user interface, as described in the specification, and is construed as a conventional computer element. “A graphic user interface so a user can select data merely recites a generic computer component and does not contribute an inventive concept to the claim. Graphical user interfaces that allow a user to select and enter information describe purely conventional features on the disclosed devices.” (Affinity Labs v. DIRECTV).
The claims further recite displaying real-time progress of the combination of models. For example, which model is currently processing data and the remaining time for the processing may be displayed. This is an insignificant extra-solution activity – i.e. merely presenting results of the abstract process of collecting and analyzing information as an ancillary part of such collecting and analysis.
Nothing in the claim recites specific limitations directed to an improved computer system, processor, memory, network, database or Internet. Similarly, the specification is silent with respect to these kinds of improvements. A general purpose computer that applies a judicial exception by use of conventional computer functions, as is the case here, does not qualify as a particular machine, nor does the recitation of a generic computer impose meaningful limits in the claimed process. (see Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716-17 (Fed. Cir. 2014)). As such, the additional elements recited in the claim do not integrate the abstract filtering process into a practical application of that process.
STEP 2B
The additional elements identified above do not amount to significantly more than the abstract filtering process.
The recited “buttons” displayed on a user interface for manual user selection of speed-prioritized or accuracy-prioritized models are generic computer components. The recited “displaying” is performed on a generic user interface, as described in the specification, and is construed as a conventional computer element. “A graphic user interface so a user can select data merely recites a generic computer component and does not contribute an inventive concept to the claim. Graphical user interfaces that allow a user to select and enter information describe purely conventional features on the disclosed devices.” (Affinity Labs v. DIRECTV).
Similarly, display the progress of an analytical process is purely conventional. It is well known to display “progress bars” for processing tasks, a fact for which Examiner takes Official Notice.
The additional structural elements or combination of elements in the claims, other than the abstract idea per se, amount to no more than a recitation of generic computer structure (i.e. a medical information processing apparatus comprising processing circuitry; a non-transitory computer-readable medium having recorded thereon a plurality of computer-executable instructions ). Each of the above components are disclosed in the specification as being purely conventional and/or known in the industry. Because the specification describes these additional elements in general terms, without describing particulars, Examiner concludes that the claim limitations may be broadly, but reasonably construed, as reciting well-understood, routine and conventional computer components and techniques. The specification describes the elements in a manner that indicates that they are sufficiently well-known that the specification does not need to describe the particulars in order to satisfy U.S.C. 112. Considered as an ordered combination the limitations recited in the claims add nothing that is not already present when the steps are considered individually. As such, the additional elements recited in the claim do not provide significantly more than the abstract filtering process, or an inventive concept.
The dependent claims add additional features including:
those that merely serve to further narrow the abstract idea above such as:
further limiting the condition to speed or accuracy (Claim 3);
further limiting the type of information (Claim 4);
those that recite additional abstract ideas such as:
calculate processing time and estimation accuracy (Claim 7); - math;
determining a combination of trained models based on user selections; (Claim 13);
switching execution to an additional trained model upon user selection in a GUI; (Claim 14);
those that recite well-understood, routine and conventional activity or computer functions such as:
determining the combination of trained models using a trained neural network; (Claim 12); - “apply it”;
display information of a selected model (Claim 6);
display the model and processing time/accuracy in association (Claim 7);
display a user interface for inputting user selections; (Claim 13);
those that recite insignificant extra-solution activities such as:
generate a trained set model; and input data to the trained set model to output the combination of trained models (Claims 8, 9); - apply it
or those that are an ancillary part of the abstract idea.
Examiner takes Official Notice that generating a trained model using historical outcomes is old and well-known and purely conventional.
The limitations recited in the dependent claims, in combination with those recited in the independent claims add nothing that integrates the abstract idea into a practical application, or that amounts to significantly more. These elements merely narrow the abstract idea, recite additional abstract ideas, or append conventional activity to the abstract process. As such, the additional element do not integrate the abstract idea into a practical application, or provide an inventive concept that transforms the claims into a patent eligible invention.
The apparatus claims are no different from the method claims in substance. “The equivalence of the method, system and media claims is readily apparent.” “The only difference between the claims is the form in which they were drafted.” (Bancorp). The method claims recite the abstract idea implemented on a generic computer, while the apparatus claims recite generic computer components configured to implement the same idea. Specifically, Claims 1, 3, 4, 6 - 9 and 11 - 14 merely add the generic hardware noted above that nearly every computer will include. The apparatus claim’s requirement that the same method be performed with a programmed computer does not alter the method’s patentability under U.S.C. 101 (In re Grams). Therefore, the claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
The Prior Art
The prior art does not teach or suggest a method and apparatus for selecting a combination of trained models that satisfies a condition, where a plurality of trained models are prepared for each for step of a plurality of steps, and one of the prepared trained models is selected for each of the plurality of steps to form the combination of trained models.
Response to Arguments
Applicant's arguments filed 14 November, 2025 with respect to the U.S.C. § 101 rejection have been fully considered but they are not persuasive.
Applicant asserts that Claim 1 is directed to “a specific technical solution to a specific technical problem” as described in the Background. The Background describes how in a medical setting different cases may require a trained model that processes patient data for either urgency or accuracy. The invention determines a combination of trained models that “meets the needs of a user”. Selecting a model that matches a user’s requirement for speed or accuracy is not a technological problem.
Applicant further asserts that Claim 1 integrates any abstract idea into a practical application by providing a user interface with buttons that “provides a specific technical solution to the specific technical problem of determining the right combination of models for a particular application.” Selecting a model that matches a user’s requirement for speed or accuracy is not a technological problem. The recited user interface is construed as a conventional computer element. “A graphic user interface so a user can select data merely recites a generic computer component and does not contribute an inventive concept to the claim. Graphical user interfaces that allow a user to select and enter information describe purely conventional features on the disclosed devices.” (Affinity Labs v. DIRECTV).
Applicant asserts that the acquiring step is not a mental process and should not be designated as an abstract idea. Applicant notes that acquiring is routinely classified as data gathering. Examiner agrees, noting that both interpretations may be applied. In particular, Electric Power Group found that collecting information, including when limited to particular content, as within the realm of abstract ideas. Nonetheless, if acquiring is data gathering, then it must also be conventional. In this respect, the specification discloses obtaining the information from a records system – i.e. a conventional computer function.
Applicant asserts that determining a model for each step cannot be performed in the human mind. Examiner disagrees. The claims require determining a model for each step that satisfies a condition according to patient information and the environmental information. Notably, the claims to not require determining a condition according to patient information and the environmental information, only using the condition, determined though some unclaimed process, to determine the combination of models by comparing the condition to the processing speed and accuracy recorded for the plurality of models. If “speed” is to be prioritized, the model that requires the shortest processing time is selected; and if “accuracy” is to be prioritized, the model that has the highest accuracy is selected (@ 0040). Data relative to the each model is stored in memory including “estimation accuracy and processing time” (@ 0074); and a combination of trained models are suggested based on the accuracy and processing time required by a task (@ 0076) and a user selects a model that responds to their needs. Selecting a model by comparing models having a known accuracy and speed to a user’s requirement for accuracy or speed, is an ordinary mental process.
CONCLUSION
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US PGPUB 2019/0008461 A1 to Gupta et al. discloses selecting machine learning models based on characteristics of the model such as speed or accuracy.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to John A. Pauls whose telephone number is (571) 270-5557. The Examiner can normally be reached on Mon. - Fri. 8:00 - 5:00 Eastern. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Robert Morgan can be reached at (571) 272-6773.
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/JOHN A PAULS/Primary Examiner, Art Unit 3683
Date: 29 December, 2025