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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 03/05/2026 has been entered.
Response to Amendment
Amendment received on 03/05/2026 is acknowledged and entered. Claims 5-6, 11-12 and 20 have been previously canceled. Claims 2-3, 10, 15, 17 have been currently canceled. Claims 1, 9 and 16 have been amended. New claim 21 has been added. Claims 1, 4, 7-9, 13-14, 16, 18-19 and 21 are currently pending in the application.
Claim Rejections under 35 USC § 103 have been withdrawn due to the Applicant’s amendment.
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, 7-9, 13-14, 16, 18-19 and 21 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 Memorandum of August 4, 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 9 is directed to a statutory category, because a series of steps satisfies the requirements of a process (a series of acts).
Claim 16 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 9 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more of updating. The claim recites:
9. A method for generating synthetic patient data, the method comprising:
receiving patient data from one or more patient data monitoring devices, wherein the one or more patient data monitoring devices include a thermal camera, and wherein the patient data includes a thermal image captured by the thermal camera;
analyzing the patient data including the thermal image in real-time to learn one or more characteristics through extraction of at least one of thermal measurement, a respiration measurement, or a position measurement of the patient;
inputting the one or more characteristics of the patient data into an artificial intelligence algorithm to generate synthetic patient data based on the one or more characteristics, the synthetic patient data including data points distributions representative of the patient data without including actual data points from the patient data, and the synthetic patient data including at least one of a synthetic temperature measurement, a synthetic respiration measurement, or a synthetic position measurement; and
storing the synthetic patient data in a database for use as training data for building a machine learning model without storing the thermal image.
The recited limitations, as currently presented, 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 mathematical concepts, but for the recitation of generic computer components. The mental processes recited in the claims, which can be performed mentally by a human analyst or using a generic computer are: analyzing patient data; learning characteristics from thermal images; extracting temperature, respiration, and position measurement; generating synthetic data based on learned characteristics. The mathematical concepts covered by the claim, which are implemented utilizing mathematical models and statistical computations, are: artificial intelligence algorithm; learning characteristics; generating synthetic data representing statistical distribution; creating synthetic measurements.
Thus, other than reciting “by a processor,” nothing in the claim element precludes the step from practically being performed in the mind, and/or mathematical concepts. 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 mathematical 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). Here, the claimed subject matter is directed to the abstract idea of manipulating existing information (e.g., “patient data”) to generate additional information (e.g., “synthetic data”). See id. 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).
As per the use of artificial intelligence and/or machine learning techniques (AI/ML) as recited in dependent 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 machine learning to simulating data, an activity predating computers, did not transform the abstract idea into a patent-eligible invention.
It is similar to other abstract ideas held to be non-statutory by the courts. See, also, 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; and 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/or 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 9, 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. 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.
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. 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 claim does not improve, e.g., operation of the thermal camera; image acquisition; computer architecture; database technology; AI training efficiency; or any other technological process. Instead, the claim merely uses computers as a tool for data processing. As to the limitation of “without storing the thermal image,” this recitation appears directed toward privacy or data management rather than improving computer technology itself.
Thus, 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.
Regarding the use of AI/ML techniques per se, 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, generating synthetic data based on the patient data 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 pending 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.
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.
Thus, claim 9 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. Based on the Specification (e.g. [0042]; [0043]; [0047]), the invention utilizes existing, conventional sensors, 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.
Also, the method uses thermal camera, monitoring devices, AI algorithm, and real-time processing. These components are all conventional computer components performing their expected functions. E.g., generating synthetic data for ML
Specifically, regarding the recited functions, MPEP 2106.05(d)(II) defines said functions as routine and conventional, or as insignificant extra-solution activity:
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) (“Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink.” (emphasis added));
ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) (“The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.”); collecting and comparing known information in Classen 659 F.3d 1057, 100 U.S.P.Q.2d 1492 (Fed. Cir. 2011)
iii. Electronic recordkeeping, Alice Corp., 134 S. Ct. at 2359, 110 USPQ2d at 1984 (creating and maintaining “shadow accounts”); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;
v. Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d 1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir. 2014) (optical character recognition); and
vi. A web browser’s back and forward button functionality, Internet Patent Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015).
Regarding training a model, said steps are nothing more than an attempt to recycle preexisting AI/ML technologies to apply for a particular health-related applications. 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. Claim 9 neither specifies a specific technical purpose for which the method is used, nor the claim defines 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 dependent claims and described in the Specification is conventional, and 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”.
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.
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.
Further, 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 1 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 9 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).
Further, there are no improvements in said machine learning 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 techniques. Said machine learning 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. However, machine learning subject matter becomes patent-eligible only when it achieves a technical purpose and, at minimum, offers a technical effect that does more than performing the solution more quickly or efficiently. The general application of machine learning techniques to solve a problem predictably is not eligible for patentability.
Moreover, there is no transformation recited in the claim as understood in view of 35 USC 101. The steps of receiving patient data; analyzing the data; generating synthetic data, and storing the synthetic data 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 “receiving patient data from one or more patient data monitoring devices;” 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 a particular technological environment is, without more, insufficient to transform the claim into patent-eligible applications of the abstract idea at their core.
Accordingly, claim 9 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 13-14 further narrow the abstract idea but do not make the claims any less abstract. Dependent claims 13-14 each merely add further details of the abstract steps recited in claim 9 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 10 and 13-15 are also directed to non-statutory subject matter.
Because Applicant’s apparatus claims 1, 4, 7-8, 21 and computer-readable storage medium claims 16, 18-19 add nothing of substance to the underlying abstract idea, they too are patent ineligi-ble under §101.
Response to Arguments
Applicant's arguments filed 03/05/2026 have been fully considered but they are not persuasive.
Applicant argues that the amended claims provide technical improvement, integrate any recited judicial exception into a practical application, recite significantly more, and, similar to Ex Parte Desjardins and DDR, are patent eligible.
Examiner respectfully disagrees and maintains, that other than reciting “by a processor,” or generic hardware elements nothing in the claim element precludes the step from practically being performed in the mind, and/or as mathematical concepts. 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. 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. The claim does not improve, e.g., operation of the thermal camera; image acquisition; computer architecture; database technology; AI training efficiency; or any other technological process. Instead, the claim merely uses computers as a tool for data processing. As to the limitation of “without storing the thermal image,” this recitation appears directed toward privacy or data management rather than improving computer technology itself. Thus, 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.
Regarding the use of AI/ML techniques per se, 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, generating synthetic data based on the patient data 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 pending 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, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Based on the Specification, the method uses generic processor, thermal camera, monitoring devices, AI algorithm, and real-time processing. These components are all conventional computer components performing their expected functions. E.g., generating synthetic data for ML. Furthermore, utilizing a trained model is nothing more than an attempt to recycle preexisting AI/ML technologies to apply for a particular health-related applications. 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. Claim 9 neither specifies a specific technical purpose for which the method is used, nor the claim defines 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.
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. Therefore, 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.
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. Notably, the Specification only briefly mentions machine learning technology in paragraphs [0020]; [0022]; [0023]; [0033]. No specific algorithm or improvement thereof discussed in the Specification, just general reference to AI/ML. Thus, the use of a trained machine learning model, as disclosed in the Specification and recited in the claims, does not integrate the abstract idea into a practical application, and does not provide substantially more.
Regarding “analyzing the patient data including the thermal image in real-time to learn one or more characteristics through extraction of at least one of thermal measurement, a respiration measurement, or a position measurement” recitation, in Content Extraction & Transmission LLC v. Wells Fargo Bank, National Ass’n, Nos. 13-1588,-1589, 14-1112, -1687 (Fed. Cir. Dec. 23, 2014) (Content Extraction) the Federal Circuit affirmed that limitations such as parsing and extracting the data 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.” 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. Id. at 8. Mental processes, e.g., parsing and extracting data, as recited in claim 1, remain unpatentable even when automated to reduce the burden on the user of what once could have been done with pen and paper. CyberSource Corp. at 1375 (“That purely mental processes can be unpatentable, even when performed by a computer, was precisely the holding of the Supreme Court in Gottschalkv. Benson, [409 U.S. 63 (1972)].”).
Similar to Content Extraction, the current claims steps including “analyzing the patient data including the thermal image in real-time to learn one or more characteristics through extraction” drawn to the basic concept of data recognition and storage, even though they recited a gfeneric thermal camera.
The Examiner further notes that it also is insufficient, without more, to establish patent eligibility that “[t]he human mind is not equipped to execute the claimed method. Although “a method that can be performed by human thought alone is merely an abstract idea and is not patent-eligible under § 101,” CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011), it does not automatically follow that methods requiring physical components, i.e., methods that arguably cannot be performed entirely in the human mind, are, therefore, not directed to abstract ideas. See, e.g., In re TLI Commc'ns LLC Patent Litig., 823 F.3d 607, 611 (Fed. Cir. 2016) (“[N]ot every claim that recites concrete, tangible components escapes the reach of the abstract-idea inquiry.”); FairWarning IP, LLC v. Latric Sys., Inc., 839 F.3d 1089, 1098 (Fed. Cir. 2016) (“[T]he inability for the human mind to perform each claim step does not alone confer patentability.”).
Regarding Enfish argument, claim 9 of the current application does not provide specific improvements in computer capabilities. In Enfish, Court found that claims are directed to a specific improvement to the way computers operate, - a particular database technique - in how computers could carry out one of their basic functions of storage and retrieval of data. The present case is different: the focus of the claims is not on such an improvement in computers as tools, but on certain independently abstract ideas that use computers as tools. There is no technological improvement described in the current application; the recited steps of receiving patient data; analyzing the data; generating synthetic data, and storing the synthetic data do not improve the functioning of computers itself, including of the processor(s) or the network elements; do not recite physical improvements in the claim, like a faster processor or more efficient memory, and do not provide operational improvement, like mathematical computation that improve the functioning of the computer. The claimed invention merely utilizes conventional computing and network elements for transmitting and storing data. Thus, the current application’ solution to the problem of generating and storing the synthetic patient data is not technological, but “business solution”, or “entrepreneurial. Accordingly, claim 9 does not provide a specific means or method that improves the relevant technology, but, instead, is directed to a result or effect that itself is the abstract idea and merely invoke generic processes and machinery.
Further, in comparison to the decision in DDR, the claims at issue remain ineligible. In DDR, the claim includes additional elements of "1) stor[ing] 'visually perceptible elements' corresponding to numerous host Web sites in a database, with each of the host Web sites displaying at least one link associated with a product or service of a third-party merchant, 2) on activation of this link by a Web site visitor, automatically identif[ying] the host, and 3) instruct[ing] an Internet web server of an 'outsource provider' to construct and serve to the visitor a new, hybrid Web page that merges content associated with the products of the third-party merchant with the stored 'visually perceptible elements' from the identified host Web site." The court held that, unlike in Ultramercial, the claim does not generically recite "use the Internet" to perform a business practice, but instead recites a specific way to automate the creation of a composite Web page by an outsource provider that incorporates elements from multiple sources in order to solve a problem faced by Web sites on the Internet.
Contrary to DDR, Applicant does not identify any problem particular to computer networks and/or the Internet that claim 9 overcomes. Instead, based on the Specification teachings, claim 9 uses a conventional, general purpose computer and thermal camera to perform generic computer functions, i.e., accessing memory, receiving and storing data, processing to transform some data, and outputting data. While the claims are set within an electronic commerce environment, claim 1 addresses a business challenge that is not particular to the Internet.
Further, in comparison to BASCOM Global Internet Services, Inc. v. AT&T Mobility LLC (Fed. Cir. 2016)(BASCOM), the claims at issue remains ineligible. In BASCOM, the Federal Circuit seemed to focus on the "technical aspects" of the claimed invention and stated that while filtering content on the Internet was already a known concept, the patent describes how its particular arrangement of elements is a technical improvement over prior art ways of filtering such content (e.g., prior art filters were either susceptible to hacking and dependent on local hardware and software, or confined to an inflexible one size-fits-all scheme). “An inventive concept may be found in the non-conventional and non-generic arrangement of the additional elements, i.e., the installation of a filtering tool at a specific location, remote from the end-users, with customizable filtering features specific to each end user.”
Contrary to BASCOM, claim 1 does not include any recitation directed to the non-conventional and non-generic arrangement of the additional elements. Claim 9 requires only a generic processor and a conventional thermal camera for receiving, processing, and storing data. These generic computer elements are recited at a high level of generality and perform the basic functions of a computer (in this case, performing a mathematical operation, receiving/transmitting and storing data) that would be needed to apply the abstract idea via a computer. Merely using generic computer components to perform the above identified basic computer functions (transmitting, generating and computing data) to practice or apply the judicial exception does not constitute a meaningful limitation that would amount to significantly more than the judicial exception.
Further, compare to McRO, Inc. dba Planet Blue v. Bandai Namco Games America Inc., 120 USPQ2d 1091 (Fed. Cir. 2016) (McRO), claim 9 does not recite any improvement of a technical field. The claims in McRO aim to automate a 3-D animator’s tasks, specifically, determining when to set keyframes and setting those keyframes, which is accomplished through rules that are applied to the timed transcript to determine the morph weight outputs, wherein said rules configured to produce more realistic speech by ‘taking into consideration the differences in mouth positions for similar phonemes based on context.’” Thus, the basis for the McRO Court’s decision was that the claims were directed to an improvement in computer-related technology (allowing computers to produce ‘accurate and realistic lip synchronization and facial expressions in animated characters’ that previously could only be produced by human animators).” The specification in McRO underlined how the claimed rules enabled the automation of specific animation tasks that previously could not be automated.
Contrary to claims in McRO, claim 9 does not recite any improvement in computer-related technology; there is no improvements in the operation of a computer or a thermal camera per se, there is no improvements claimed as a set of ‘rules’ (basically mathematical relationships) that improve computer-related technology by allowing computer performance of a function not previously performable by a computer.” The claimed steps of receiving patient data; analyzing the data; generating synthetic data, and storing the synthetic data represent a collection of conventional steps performed by a computer - receiving data, manipulating data, and storing the manipulated data. Claim 9 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 recited steps on a set of generic computer components. Nothing in the claim, understood in light of the Specification, requires anything other than off-the-shelf, conventional computer, thermal camera and a memory for gathering, processing and storing the desired information. Said computing elements are recited at a high level of generality and perform the basic functions of a computer, such as performing a mathematical operation and receiving and outputting data, that would be needed to apply the abstract idea via computer. Therefore, claim 9 does not include any recitation that improve computer-related technology by allowing computer performance of a function not previously performable by a computer.”
Applicant's arguments with respect to prior art rejections have been considered but are moot, the prior art rejections have been withdrawn.
Citations of pertinent art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Andre Goncalves et al. “Generation and evaluation of synthetic patient data” BMC Medical Research Methodology (2020) 20:108; pp. 1-40, - discloses synthetic patient records; statistical distribution; privacy preservation; ML training database.
Andrew Yale et al. “Privacy Preserving Synthetic Health Data” ESANN2019-European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2019, Bruges, Belgium. ⟨hal-02160496 ⟩ pp.1-10, - discloses GAN-generated synthetic healthcare data; no disclosure of original patient records; preservation of distributions; AI training.
Distinguishable Subject Matter
The present claims remain distinguishable from the prior art of record. While cited references disclose receiving patient thermal image from patient data monitoring devices, analyzing the thermal image in real-time, to learn characteristics through extraction of thermal measurement, a respiration measurement, or a position measurement of the patient; based on said characteristics generating synthetic patient data, and storing the synthetic patient data in a database for use as training data for building a machine learning model without storing the thermal image, the prior art of record 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
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Igor Borissov whose telephone number is 571-272-6801. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor Kambiz Abdi can be reached on 571-272-6702. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/IGOR N BORISSOV/Primary Examiner, Art Unit 3685 7/21/2026
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