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
Amendment received on 06/09/2026 is acknowledged and entered. Claims 3 and 9-20 have been canceled. Claims 1-2 and 4-7 have been amended. New claims 21-33 have been added. Claims 1-2, 4-8, and 21-33 are currently pending in the application.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/07/2026 is being considered by the examiner. The submission is in compliance with the provisions of 37 CFR 1.97.
Claim Rejections - 35 USC § 102
Claim Rejections under 35 USC §102 have been withdrawn due to the Applicant’s amendment.
Claim Objections
Claim 21 and 28 are objected to because the claims are missing a period (“.”) at the end of the claims. Thus, the scope of the claims is confusing.
Further, regarding claim 28, the Examiner recommends the following language for claiming a “computer program product”:
“A non-transitory computer readable medium having computer-readable instructions stored therein, which when executed by a processor cause the processor to perform a method, comprising:”
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-2, 4-8, and 21-33 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
In determining whether a claim falls within an excluded category, the Examiner is guided by the Court’s two-part framework, described in Mayo and Alice. Id. at 217-18 (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 75-77 (2012)); Bilski v. Kappos, 561 U.S. 593, 611 (2010); 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019); the October 2019 Update of the 2019 Revised Guidance (Oct. 17, 2019); 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence (July 17, 2024), and the USPTO’s Paten Subject Matter Eligibility Memorandums of August 4, 2025 and December 5, 2025.
Step 1
Claims are eligible for patent protection under § 101 if they are in one of the four statutory categories and not directed to a judicial exception to patentability (i.e., laws of nature, natural phenomena, and abstract ideas). Alice Corp. v. CLS Bank Int'l, 573 U. S. ____ (2014).
The broadest reasonable interpretation of claim 1 encompasses a computer system (e.g., hardware such as a processor and memory) that implements the recited functions. If assuming that the system comprises a device or set of devices, then the system is directed to a machine, which is a statutory category of invention.
Claim 21 is directed to a statutory category, because a series of the recited steps satisfies the requirements of a process (a series of acts).
Claim 28 is directed to a statutory category, because a non-transitory computer-readable medium comprising computer-readable instructions satisfies the requirements of a product. (Step 1: Yes).
Next, the claim is analyzed to determine whether it is directed to a judicial exception.
Step 2A – Prong 1
Claim 21 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more of receiving and presenting information. The claim recites:
21. A computer-implemented method, comprising:
generating, by a system comprising at least one processor, based on monitoring interactions of a caregiver with a group of patients' medical information, training data
comprising labels indicating relative importance of respective medical information of the group of patients medical information;
training, by the system, using the training data, a machine learning model to generate summaries of patient medical information for the caregiver, wherein the summaries provide portions the patient medical information predicted to be most important to the caregiver;
vectoring content of a patient's medical information to generate a first vectored content, wherein the patient's medical information comprises patient data, medical data, and medical images associated with the patient;
identifying, by the system, based on the first vectored content, second vectored content in a digital library comprising medical condition information, wherein the digital library comprises vectored representations of respective medical conditions, and wherein a medical condition defined by the second vectored content is assigned to the patient based on threshold similarity between the first vectored content and the second vectored content;
generating, by the system, using the machine learning model, a summary of the medical condition of the patient based on the first vectored content and the second vectored content, wherein the summary comprises information from the patient's medical information and the medical condition information that controls which portions of the patient's medical information are initially presented; and
presenting, by the system, the summary on a summary screen of a graphical user interface, the summary screen being distinct from an all data screen of the graphical user interface configured to present all of the patient's medical information, wherein the summary screen comprises at least one image region and at least one text region, and wherein the summary and at least one medical image associated with the patient are concurrently presented within the image region and the text region to facilitate subsequent investigation of the patient's medical condition without requiring initial review of the all data screen.
The recited limitations, e.g., vectorization, similarity processing, ML training, presenting, etc., as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, which may be practically performed in the human mind using observation, evaluation, judgment, and opinion (MPEP 2106.04(a)(2), subsection III), and/or certain methods of organizing human activity, such as following rules or instructions, but for the recitation of generic computer components. Other than reciting “by a processor,” nothing in the claim element precludes the step from practically being performed in the mind, and/or performed as organized human activity. Aside from the general technological environment (addressed below), it covers purely mental concepts and/or certain methods of organizing human activity processes, and the mere nominal recitation of a generic network appliance (e.g. an interface for inputting or outputting data, or generic network-based storage devices and displays) does not take the claim limitation out of the mental processes and/or certain methods of organizing human activity grouping.
Specifically, the utilizing statistical tools to process data and to output the estimated values - said functions could be performed by a human using mental steps or basic critical thinking, which are types of activities that have been found by the courts to represent abstract ideas (e.g., mental comparison regarding a sample or test subject to a control or target data in Ambry, Myriad CAFC, or the diagnosing an abnormal condition by performing clinical tests and thinking about the results in In re Grams, 888 F.2d 835 (Fed. Cir. 1989) (Grams)). In Grams, the recited functions require obtaining data or patient information (from sensors), and analyze that data to ascertain the existence and identity of an abnormality or estimated responses, and possible causes thereof. While said functions are performed by a computer, they are in essence a mathematical algorithm, in that they represent "[a] procedure for solving a given type of mathematical problem." Gottschalk v. Benson, 409 U.S. 63, 65, 93 S.Ct. 253, 254, 34 L.Ed.2d 273 (1972). Moreover, the Federal Circuit has held, “without additional limitations, a process that employs mathematical algorithms to manipulate existing information to generate additional information is not patent eligible.” Digitech Image Techs., LLC v. Elecs. for Imaging, Inc., 758 F.3d 1344, 1351 (Fed. Cir. 2014). Further, “analyzing information by steps people go through in their minds, or by mathematical algorithms, without more, [are] essentially mental processes within the abstract-idea category.” Elec. Power, 830 F.3d at 1354; see also Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1146 (Fed. Cir. 2016). “[T]he fact that the required calculations could be performed more efficiently via a computer does not materially alter the patent eligibility of the claimed subject matter.” Bancorp Servs., L.L.C. v. Sun Life Assurance Co. of Can. (U.S.), 687 F.3d 1266, 1278 (Fed. Cir. 2012).
Regarding the use of artificial intelligence and/or machine learning techniques (AI/ML), as recited in other claims, said recitation does not make the claim patent eligible, because said tools are utilized merely for data gathering and comparing, and are not utilized in express manipulation and control of functional aspects and/or hardware components/equipment of real-world processes and systems using output of AI models (e.g., manufacturing processes and equipment, medical treatments, communications processes and systems, logistics systems and hardware, interactive smart phone apps, etc.).
It is similar to other abstract ideas held to be non-statutory by the courts. See, also, Recentive Analytics, Inc. v. Fox Corp. (Fed. Cir. 2025), wherein the court noted that "iterative training," a claimed feature, was inherent to all machine learning models and thus did not confer eligibility. Additionally, applying AI/ML techniques to analyzing of a medical condition of a patient, an activity predating computers, did not transform the abstract idea into a patent-eligible invention. Furthermore, the claim is analogous to claims in Content Extraction & Transmission LLC v. Wells Fargo Bank, National Ass’n, Nos. 13-1588,-1589, 14-1112, -1687 (Fed. Cir. Dec. 23, 2014), which were generally directed to “the abstract idea of 1) collecting data, 2) recognizing certain data within the collected data set, and 3) storing that recognized data in a memory.” Slip op. at 7. The Court explained that ”[t]he concept of data collection, recognition, and storage is undisputedly well-known,” and noted that “humans have always performed these functions.” Id. The Court then rejected CET’s argument that the claims were patent eligible because they required hardware to perform functions that humans cannot, such as processing and recognizing the stream of bits output by the scanner. Comparing the asserted claims to “the computer-implemented claims in Alice,” the Court concluded that the claims were “drawn to the basic concept of data recognition and storage,” even though they recited a scanner. See, also, Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363 (Fed. Cir. 2015)—tailoring sales information presented to a user based on, e.g., user data and time data; TLI Communications LLC v. AV Automotive LLC 823 F.3d 607, 118 U.S.P.Q.2d 1744 (Fed. Cir. 2016) - recording, transmitting and administering digital images; DataTreasury Corp. v. Fidelity National Information Services 669 Fed. Appx. 572 (Fed. Cir. 2016) - remote image capture with centralized processing and storage; RecogniCorp LLC v. Nintendo Co. 855 F.3d 1322, 122 U.S.P.Q.2d 1377 (Fed Cir. 2017) - encoding and decoding image data; Intellectual Ventures I LLC v. Erie Indemnity Co. 850 F.3d 1315, 121 U.S.P.Q.2d 1928 (Fed Cir. 2017) - mobile interface for accessing remotely stored documents, and retrieving data from a database using an index of XML tags and metafiles.
As per receiving, storing and outputting data limitations, it has been held that “As many cases make clear, even if a process of collecting and analyzing information is ‘limited to particular content’ or a particular ‘source,’ that limitation does not make the collection and analysis other than abstract.” SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161, 1168 (Fed. Cir. 2018) (citation omitted); see also In re Jobin, 811 F. App’x 633, 637 (Fed. Cir. 2020) (claims to collecting, organizing, grouping, and storing data using techniques such as conducting a survey or crowdsourcing recited a method of organizing human activity, which is a hallmark of abstract ideas).
All these cases describe the significant aspects of the claimed invention, albeit at another level of abstraction. See Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1240-41 (Fed. Cir. 2016) ("An abstract idea can generally be described at different levels of abstraction. As the Board has done, the claimed abstract idea could be described as generating menus on a computer, or generating a second menu from a first menu and sending the second menu to another location. It could be described in other ways, including, as indicated in the specification, taking orders from restaurant customers on a computer.").
Therefore, if a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” and/or “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. (Step 2A – Prong 1: Yes).
Step 2A – Prong 2
In Prong Two, the Examiner determines whether claim 21, as a whole, recites additional elements that integrate the judicial exception into a practical application of the exception, i.e., whether the additional elements apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is no more than a drafting effort designed to monopolize the judicial exception. See Guidance, 84 Fed. Reg. at 54-55. If the additional elements do not integrate the judicial exception into a practical application, then the claim is directed to the judicial exception. See id., 84 Fed. Reg. at 54. “An additional element [that] reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field” is indicative of integrating a judicial exception into a practical application. See Guidance, 84 Fed. Reg. at 55.
The Examiner determined that this judicial exception is not integrated into a practical application, because there are no meaningful limitations that transform the exception into a patent eligible application. In particular, the claim recites additional elements – using a processor to perform the recited steps. However, the processor in each step is recited (or implied) at a high level of generality, i.e., as a generic processor performing a generic computer functions of processing data, including receiving, storing, comparing, and outputting data. This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f). The processor that performs the recited steps merely automates these steps which can be done mentally or manually.
Specifically, the limitation of “vectoring content” is very broad, and does not specify how vectorization is performed, or what technical problem it solves. Further, the “vector embeddings” and “similarity thresholds” are conventional techniques in information retrieval and machine learning. And predicting what portions of the patient’s medical information are likely to be important to a particular caregiver based on importance indicating labels is nothing more than observing user behavior, inferring preferences, training a model, and personalizing information presentation. Again, that is an information-personalization concept rather than a technological improvement. As per “…presented ….to facilitate subsequent investigation …without requiring initial review of all data screen” represents a business workflow advantage, not technological. Again, “facilitating review” is a human benefit, and is not a technological improvement.
Regarding the use of AI/ML techniques, said steps are nothing more than an attempt to recycle preexisting AI/ML technologies to apply for a particular computing application. There are no improvements in said AI/ML techniques, such as advances in the field of computer science itself, or designing a new neural network, and there is no controlling of a technological process using the outcome of said AI/ML operations.
Thus, the use of a trained machine learning model does not integrate the abstract idea of limitation into a practical application, because, under its broadest reasonable interpretation when read in light of the Specification, analyzing importance of patient’s medical records and generating summaries of important information encompasses mental processes practically performed in the human mind by observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. Similar to Recentive Analytics, the remaining claims recite conventional machine learning models without specific improvements to the technology itself. The court noted that "iterative training," a claimed feature, was inherent to all machine learning models and thus did not confer eligibility. The pending claims do not articulate "how" a technological improvement is achieved.
Further, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually; there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, their collective functions merely provide conventional computer implementation. The combination of generating vectors, calculating similarity, and applying a threshold is insufficient to establish a technological improvement. None of the additional elements "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment,' that is, implementation via computers." Alice Corp., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)).
The recited steps do not control or improve operation of a machine (MPEP 2106.05(a)), do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and do not apply the judicial exception with, or by use a particular machine (MPEP 2106.05(b)), but, instead, require receiving, storing, comparing and outputting data.
Thus, while the additional elements have and execute instructions to perform the abstract idea itself, this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." The claim only manipulates abstract data elements into another form, and does not set forth improvements to another technological field or the functioning of the computer itself and, instead, uses computer elements as tools in a conventional way to improve the functioning of the abstract idea identified above.
As per receiving, storing and/or outputting data limitations, these recitations amount to mere data gathering and/or outputting, is insignificant post-solution or extra-solution component and represents nominal recitation of technology. Insignificant "post-solution” or “extra-solution" activity means activity that is not central to the purpose of the method invented by the applicant. However, “(c) Whether its involvement is extra-solution activity or a field-of-use, i.e., the extent to which (or how) the machine or apparatus imposes meaningful limits on the execution of the claimed method steps. Use of a machine or apparatus 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 weigh against eligibility”. See Bilski, 138 S. Ct. at 3230 (citing Parker v. Flook, 437 U.S. 584, 590, 198 USPQ 193, ___ (1978)). Thus, claim drafting strategies that attempt to circumvent the basic exceptions to § 101 using, for example, highly stylized language, hollow field-of-use limitations, or the recitation of token post-solution activity should not be credited. See Bilski, 130 S. Ct. at 3230.
Therefore, claim 17 as a whole, outputs only data structure, - everything remains in the form of a code stored in the computer memory. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore, the claim is directed to an abstract idea. (Step 2A – Prong 2: No).
Step 2B
If a claim has been determined to be directed to a judicial exception under revised Step 2A, examiners should then evaluate the additional elements individually and in combination under Step 2B to determine whether the provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself).
The Examiner determined that the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the recited steps amount to no more than mere instructions to apply the exception using a generic computer component. The claim is now re-evaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field.
The method would require a processor and memory in order to perform basic computer functions of receiving information, storing the information in a database, retrieving information from the database, comparing data, and outputting said information. These components are not explicitly recited and therefore must be construed at the highest level of generality. Based on the Specification ([0139] …The processing unit 1304 can be any of various commercially available processors and may include a cache memory), the invention utilizes conventional communication networks and generic processors, which can be found in mobile devices or desktop computers, conventional memory and display devices, and the functions performed by said generic computer elements are basic functions of a computer - performing a mathematical operation, receiving, storing, comparing and outputting data - have recognized by the courts as routine and conventional activity.
Regarding the use of AM/ML techniques, said steps are nothing more than an attempt to recycle preexisting AI/ML technologies to apply for a health analysis application. There are no improvements in said AI/ML techniques, such as advances in the field of computer science itself, or designing a new neural network, and there is no controlling of a technological process using the outcome of said AI/ML operations. The pending claims neither specify a specific technical purpose for which the method is used, nor the claims define a specific technical implementation of the method, nor the claimed method is particularly adapted for that implementation in that its design is motivated by technical considerations of the internal functioning of the computer. Said AI/ML algorithms and computations are done inside of a computer, and do not have a real-world impact and are not tied to the functionality of the computer. Further, there is no evidence that the invention lies in the training phase or execution phase or both; said AI/ML recitation represents merely conventionally applying an existing model to an existing data from publicly accessible databases, with the result being not technological, but purely entrepreneurial. Similar to Recentive Analytics, Inc. v. Fox Corp. (Fed. Cir. 2025), the machine learning technology as recited in the pending claims and described in the Specification is conventional, such as, for example: [0065] “…any suitable
vectoring technology can be utilized, e.g., Euclidean distance, cosine similarity, etc. Other suitable AI/ML technologies/processes 125A-n that can be applied include, in a non-limiting list, any of vector representation via term frequency-inverse document frequency (tf-idf) capturing term/token frequency in the input data 108A-n versus terms/tokens present in medical data 196A-n, historical data 194A-n, etc. Other applicable AI/ML technologies include, in a non-limiting list, neural network embedding, layer vector representation of terms/categories (e.g., common terms having different tense), bidirectional and auto-regressive transformer (BART) model architecture,…, and suchlike”, and the processes and logic flows described in this Specification can be performed by one or more programmable processors executing one or more computer programs to perform actions by operating on input data and generating output. (Specification [0139] …The processing unit 1304 can be any of various commercially available processors and may include a cache memory.)
Thus, the background of the current application does not provide any indication that the processor is anything other than a generic, off-the-shelf computer component, and the Symantec, TLI, and OIP Techs. court decisions cited in MPEP 2106.05(d)(II) indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
Also, the claim does not involve a non-conventional and non-generic arrangement of known, conventional pieces, as asserted, by receiving information from an external source of data. The receiving of data from an external source over a network, such as via the Internet, can fairly be characterized as insignificant extra-solution activity that does not receive patentable weight. See Bilski, 545 F.3d 943, 963 (Fed. Cir. 2008) (en banc), aff’d sub nom Bilski v. Kappos, 561 U.S. 593 (2010) (characterizing data gathering steps as insignificant extra-solution activity). Similar to Content Extraction, 776 F.3d at 1347; Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 715 (Fed. Cir. 2014): “And we have recognized that merely presenting the results of abstract processes of collecting and analyzing information, without more (such as identifying a particular tool for presentation), is abstract as an ancillary part of such collection and analysis.” Here, the claims are clearly focused on the combination of those abstract-idea processes. The advance they purport to make is a process of gathering and analyzing information of a specified content, then displaying the results, and not any particular asserted inventive technology for performing those functions. They are therefore directed to an abstract idea. As such, the additional elements, considered individually and in combination with the other claim elements, do not make the claim as a whole significantly more than the abstract idea itself. The claim uses conventional ML techniques, vector similarity, and a conventional GUI to automate the human activity of determining which portion of a patient’s medical record are important and presenting those portions to a caregiver.
Accordingly, a conclusion that the recited steps are well-understood, routine, conventional activity is supported under Berkheimer Option 2. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Similar to Electric Power Group v Alstom S.A. (Fed Cir, 2015-1778, 8/1/2016) (Power Group), claim’ invocation of computers, networks, and displays does not transform the claimed subject matter into patent-eligible applications. Claim 21 does not require any nonconventional computer, network, or display components, or even a “non-conventional and non-generic arrangement of known, conventional pieces,” but merely call for performance of the claimed information collection, analysis, and display functions on a set of generic computer components and display devices. Nothing in the claim, understood in light of the specification, requires anything other than off-the-shelf, conventional computer, network, and display technology for gathering, sending, and presenting the desired information. Analogous to Power Group, claim 21 does not even require a new source or type of information, or new techniques for analyzing it. As a result, the claim does not require an arguably inventive set of components or methods, such as measurement devices or techniques that would generate new data. The claim does not invoke any assertedly inventive programming. Merely requiring the selection and manipulation of information - to provide a “humanly comprehensible” amount of information useful for users - by itself does not transform the otherwise-abstract processes of information collection and analysis into patent eligible subject matter. Merely obtaining and selecting information, by content or source, for collection, analysis, and display does nothing significant to differentiate a process from ordinary mental processes, whose implicit exclusion from § 101 undergirds the information-based category of abstract ideas. Therefore, the recited steps represent implementing the abstract idea on a generic computer, or “reciting a commonplace business method aimed at processing business information despite being applied on a general purpose computer” Versata, p. 53; Ultramerical, pp. 11-12.
Furthermore, the recited functions do not improve the functioning of computers itself, including of the processor(s) or the network elements. There are no physical improvements in the claim, like a faster processor or more efficient memory, and there is no operational improvement, like mathematical computation that improve the functioning of the computer. Applicant did not invent a new type of computer; Applicant like everyone else programs their computer to perform functions. The Supreme Court in Alice indicated that an abstract claim might be statutory if it improved another technology or the computer processing itself. Using a (programmed) computer to implement a common business practice does neither. The Federal Circuit has recognized that "an invocation of already-available computers that are not themselves plausibly asserted to be an advance, for use in carrying out improved mathematical calculations, amounts to a recitation of what is 'well-understood, routine, [and] conventional.'" SAP Am., Inc. v. InvestPic, LLC, 890 F.3d 1016, 1023 (Fed. Cir. 2018) (alteration in original) (citing Mayo v. Prometheus, 566 U.S. 66, 73 (2012)). Apart from the instructions to implement the abstract idea, they only serve to perform well-understood functions (e.g., receiving, storing, comparing and transmitting data—see the Specification as well as Alice Corp.; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016); and Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015) covering the well-known nature of these computer functions). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually; there is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. “However, it is not apparent how appellant’s programmed digital computer can produce any synergistic result. Instead, the computer will simply do the job it is instructed to do. Where is there any surprising or unexpected result? The unlikelihood of any such result is merely one more reason why patents should not be granted in situations where the only novelty is in the programming of general purpose digital computers”. See Sakraida v. Ag. Pro, Inc., 425 U.S. 273 [ 96 S.Ct. 1532, 47 L.Ed.2d 784], 189 USPQ 449 (1976) and A P Tea Co. V. Supermarket Corp., 340 U.S. 147 [ 71 S.Ct. 127, 95 L.Ed. 162], 87 USPQ 303 (1950).
Furthermore, there is no transformation recited in the claim as understood in view of 35 USC 101. The recited steps merely represent abstract ideas which cannot meet the transformation test because they are not physical objects or substances. Bilski, 545 F.3d at 963. Said steps are nothing more than mere manipulation or reorganization of data, which does not satisfy the transformation prong. It is further noted that the underlying idea of the recited steps could be performed via pen and paper or in a person's mind. Moreover, “We agree with the district court that the claimed process manipulates data to organize it in a logical way such that additional fraud tests may be performed. The mere manipulation or reorganization of data, however, does not satisfy the transformation prong.” and “Abele made clear that the basic character of a process claim drawn to an abstract idea is not changed by claiming only its performance by computers, or by claiming the process embodied in program instructions on a computer readable medium. Thus, merely claiming a software implementation of a purely mental process that could otherwise be performed without the use of a computer does not satisfy the machine prong of the machine-or-transformation test”. CyberSource, 659 F.3d 1057, 100 U.S.P.Q.2d 1492 (Fed. Cir. 2011)
Therefore, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, because, when considered separately and in combination, the claim elements do not add significantly more to the exception. Considered separately and as an ordered combination, the claim elements do not provide an improvement to another technology or technical field; do not provide an improvement to the functioning of the computer itself; do not apply the judicial exception by use of a particular machine; do not effect a transformation or reduce a particular article to a different state or thing; and do not add a specific limitation other than what is well-understood, routine and conventional in the operation of a generic computer. None of the hardware recited "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment,' that is, implementation via computers." Id., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)). As per “A computer-implemented method ” recitations, these limitations do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment, that is, implementation via computers." Id., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)). Limiting the claims to the particular technological environment is, without more, insufficient to transform the claim into patent-eligible applications of the abstract idea at their core.
Accordingly, claim 21 is not directed to significantly more than the exception itself, and is not eligible subject matter under § 101. (Step 2B: No).
Further, although the Examiner takes the steps recited in the independent claim as exemplary, the Examiner points out that limitations recited in dependent claims 22-27 further narrow the abstract idea but do not make the claims any less abstract. Dependent claims 22-27 each merely add further details of the abstract steps recited in claim 21 without including an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. These claims "add nothing of practical significance to the underlying idea," and thus do not transform the claimed abstract idea into patentable subject matter. Ultramercial, 772 F.3d at 716. Therefore, dependent claims 22-27 are also directed to non-statutory subject matter.
Because Applicant’s apparatus claims 1-2 and 4-8, and computer program product claims 28-33 add nothing of substance to the underlying abstract idea, they too are patent ineligi-ble under §101.
Response to Arguments
Applicant's arguments filed 06/09/2026 have been fully considered but they are not persuasive.
Regarding Ex Parte Desjardins (Desjardins) argument, in Desjardins the Specification identifies improvements in training the machine learning model itself, such as "effectively learn new tasks in succession whilst protecting knowledge about previous tasks," and that the claimed improvement allows artificial intelligence (AI) systems to "us[e] less of their storage capacity" and enables "reduced system complexity." And claim 1 in Desjardins, when evaluated as a whole, reflects said improvement: "adjust the first values of the plurality of parameters to optimize performance of the machine learning model on the second machine learning task while protecting performance of the machine learning model on the first machine learning task." Therefore, said recitation constitutes an improvement to how the machine learning model itself operates, and, when considered as a whole, integrates an abstract idea into a practical application.
Contrary to Desjardins, the current claims do not improve the operation, efficiency, or functionality of machine learning models, e.g., handling continual learning, reducing resource use, or solving specific technical problems like catastrophic forgetting. Further, there is no evidence that the invention lies in the training phase or execution phase or both; said machine learning recitation represents merely conventionally applying an existing model to an existing data. Based on the Specification [0065], the invention utilizes any of conventional AI/ML technologies and/or processes, conventional communication networks and generic processors. Contrary to Desjardins, the current claims do not improve the operation, efficiency, or functionality of AI/ML models, e.g., handling continual learning, reducing resource use, or solving specific technical problems like catastrophic forgetting; there is no improvement to AI/ML architecture; there is no new neural network; no improvements to computer hardware or networking. Further, there is no evidence that there is an improvement in the training phase or execution phase or both; said ML recitation represents merely conventionally applying an existing model to an existing data; the AI/ML model is used only as a prediction engine, and “retraining” step is a routine supervised learning technique rather than a technological improvement.
Regarding practical application argument, the Examiner maintains that there are no meaningful limitations that transform the exception into a patent eligible application. However, the processor in each step is recited (or implied) at a high level of generality, and this generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f). Further, the limitation of “vectoring content” is very broad, and does not specify how vectorization is performed, or what technical problem it solves; the “vector embeddings” and “similarity thresholds” are conventional techniques in information retrieval and machine learning; and predicting what portions of the patient’s medical information are likely to be important to a particular caregiver based on importance indicating labels is nothing more than observing user behavior, inferring preferences, training a model, and personalizing information presentation. Essentially, the claim recites an information-personalization concept rather than a technological improvement. As per “…presented ….to facilitate subsequent investigation …without requiring initial review of all data screen” represents a business workflow advantage, not technological. Again, “facilitating review” is a human benefit, and is not a technological improvement.
And there are no improvements in said AI/ML techniques, such as advances in the field of computer science itself, or designing a new neural network, and there is no controlling of a technological process using the outcome of said AI/ML operations.
Thus, the use of a trained machine learning model does not integrate the abstract idea of limitation into a practical application, because, under its broadest reasonable interpretation when read in light of the specification, analyzing importance of patient’s medical records and generating summaries of important information encompasses mental processes practically performed in the human mind by observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The pending claims do not articulate "how" a technological improvement is achieved.
Regarding the Inventive concept argument, the Examiner maintains that the claims utilize conventional ML techniques, vector similarity, and a conventional GUI to automate the human activity of determining which portion of a patient’s medical record are important and presenting those portions to a caregiver, and the final effect – presenting only important information – is a business improvement, not technological. Therefore, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, because, when considered separately and in combination, the claim elements do not add significantly more to the exception. Considered separately and as an ordered combination, the claim elements do not provide an improvement to another technology or technical field; do not provide an improvement to the functioning of the computer itself; do not apply the judicial exception by use of a particular machine; do not effect a transformation or reduce a particular article to a different state or thing; and do not add a specific limitation other than what is well-understood, routine and conventional in the operation of a generic computer. None of the hardware recited "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment,' that is, implementation via computers." Id., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)).
Applicant's arguments with respect to prior art have been considered but are moot, the claim rejections under 35 USC 102 have been withdrawn due to the Applicant amendment.
Citations of pertinent art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Devarakonda et al. - US 2019/0206517 A1 – disclsoes supervised learning to predict what questions of information the professional is trying to obtain; prioritizing questions according to the interaction context.
Baloor et al. - US 2015/0370979 A1 – discloses a concept of extracting the most important data items relevant to patient care from very large EMRs; extracting medical data; determining relationship between medical data and medical problems; filtering based on a threshold; prioritizing a clinical summary.
King et al. “Using machine learning to selectively highlight patient information” J Biomed Inform. 2019 Dec:100:103327. doi: 10.1016/j.jbi.2019.103327. Epub 2019 Oct 29; pp. 1-28, discloses a learning EMR configured to learn statistical models of clinician information-seeking behavior; identify relevant patient data; predict which data are relevant to the clinician’s task; and use the prediction to direct the display of data in future patients.
Distinguishable Subject Matter
The present claims remain distinguishable from the prior art of record. The prior art of record, while disclosing various features of the claimed invention, fails to disclose a specific combination of the inventive features as recited in the claims. Thus, the Examiner has not made a prior art rejection under 35 USC §102 or §103.
Conclusion
THIS ACTION IS MADE FINAL. 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 extension fee 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.
/IGOR N BORISSOV/Primary Examiner, Art Unit 3685 8/19/2026
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