DETAILED ACTION
Notice to Applicant
This communication is in response to the amendment submitted February 15, 2026. The present application claims priority under 35 U.S.C. § 119 to Korean Patent Application Nos. 10-2021-0179326, filed on December 15, 2021, and 10-2022-0086864, filed on July 14, 2022, respectively, in the Korean Intellectual Property Office. Claim 14 is amended. Claims 2, 3, and 15 were previously cancelled. Claims 21 – 23 are new. Claims 1, 4 – 14, and 16 – 23 are presented for examination.
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 .
Claim Objections
The objection to Claim 14 is withdrawn based upon the amendment submitted February 15, 2026.
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 – 14, and 16 – 23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step One
Claims 1, 4 – 14, and 16 – 23 are drawn to a system/apparatus, method, and non-transitory computer readable medium, which is/are statutory categories of invention (Step 1: YES).
Step 2A Prong One
Independent claims 1 and 7 recite an receiving a medical record of a patient and converting the received medical record into an episode list including a condition of the patient, a treatment method, and a treatment history; separate the received medical record associated with the patient into an examination record table and a treatment record table; arrange the examination record table and the treatment record table in chronological order; replace missing values in the examination record table with one of an average value, a mode value and an interpolation value of multiple time series values between treatment orders of medical record items corresponding to the missing values; and convert the received medical record into the episode list based on the examination record table and the treatment record table, wherein the episode list is a time series having an order of a first condition of the patient, the treatment method applied to the patient, a second condition of the patient after applying the treatment method, and the treatment history of the patient; and wherein the patient condition is a time series mixed probability distribution model that predicts a plurality of conditions that can be resulted in when the treatment method is applied to the patient and a probability that each of the plurality of conditions can be resulted in.
Independent claim 14 recites an receiving a medical record of a patient and converting the received medical record into an episode list including a condition of the patient, a treatment method applied to the patient, and a treatment history of the patient; separate the received medical record associated with the patient into an examination record table and a treatment record table; arrange the examination record table and the treatment record table in chronological order; replace missing values in the examination record table with one of an average value, a mode value and an interpolation value of multiple time series values between treatment orders of medical record items corresponding to the missing values; wherein the episode list is a time series having an order of a first condition of the patient, the treatment method applied to the patient, a second condition of the patient after applying the treatment method, and the treatment history of the patient; and wherein the converting of the received medical record into the episode list further includes: generating a treatment method identifier applied to the patient based on the treatment record table; generating a first condition identifier of the patient before applying the treatment method and a second condition identifier of the patient after applying the treatment method, based on the examination record table; generating a treatment history identifier of the patient after applying the treatment method based on the examination record table; and updating the episode list based on the treatment method identifier, the first condition identifier, the second condition identifier, and the treatment history identifier.
The recited limitations, as drafted, under their broadest reasonable interpretation, cover certain methods of organizing human activity, as reflected in the specification, which states that the present invention “relate[s] to and artificial intelligence apparatus for planning and exploring an optimized treatment path” (see: specification paragraph 2). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or relationships or interactions between people, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. The present claims cover certain methods of organizing human activity because it addresses a need that exists “to explore a series of treatment paths that ultimately improve a patient to the best condition, and for this, reinforcement learning technology may be used” (paragraph 5 of the published specification). Accordingly, the claims recite an abstract idea(s) (Step 2A Prong One: YES).”
Step 2A Prong Two
This judicial exception is not integrated into a practical application. The claims are abstract but for the inclusion of the additional elements include as follows:
Claim 1: “apparatus”, “module”, “electronic”, “database”, “store the episode in an episode database”, “a patient condition predictive intelligence deep learning module configured to train a patient condition predictive intelligence for predicting a following condition of the patient”, “a local policy intelligence reinforcement learning module”, “an optimized treatment path exploration module”, “global policy intelligence management module”, “predictive intelligence”
Claim 3: “apparatus”, “predictive intelligence”, “probability distribution model”
Claim 4: “apparatus”, “intelligence”
Claim 5: “apparatus”, “intelligence”, “module”, “federation message or a synchronization message”
Claim 6: “apparatus”, “intelligence”, “federation message”, “synchronization message”
Claim 7: “apparatus”, “electronic”, “training a patient condition predictive intelligence”, “performing reinforcement learning of a policy intelligence”, updating a global policy intelligence for the reinforcement learning of the policy intelligence based on the policy intelligence”, “outputting the optimized treatment path for the patient using the policy intelligence”, “reading the EMR …. and initializing the episode list”
Claim 9: “patient condition predictive intelligence”, “model”
Claim 10: “policy intelligence”; “treatment method planning intelligence”, “global policy intelligence”
Claim 11: “reinforcement learning of a policy intelligence”, “database”, “synchronizing the treatment method planning intelligence and the treatment history determination intelligence with the global treatment method planning intelligence and the global treatment history determination intelligence”
Claim 12: “database”, “intelligence”
Claim 13: “global policy intelligence”, “transmitting the global policy intelligence to the external medical institution when the message is a synchronization message”, “updating the global policy intelligence using a policy intelligence of the external medical institution provided from the external medical institution when the message is a federation message”
Claim 14: “non-transitory computer-readable medium comprising a program code that, when executed by a processor, causes the processor to execute operations of”, “electronic”, “training a patient condition predictive intelligence for predicting a following condition of the patient after applying the treatment method to the patient”, “performing reinforcement learning of a policy intelligence for exploring an optimized treatment path for the patient based on the episode”, “outputting the optimized treatment path for the patient using the policy intelligence”, “updating a global policy intelligence for exploring the optimized treatment path based on the policy intelligence”, “reading the EMR …. and initializing the episode list”
Claims 15 and 17: “non-transitory computer-readable medium”
Claim 16: “non-transitory computer-readable medium”, “patient condition predictive intelligence”, “distribution model”
Claim 18: “non-transitory computer-readable medium”, “performing of the reinforcement learning of the policy intelligence”, “data base”, “synchronizing the treatment method planning intelligence and the treatment history determination intelligence with the global treatment method planning intelligence and the global treatment history determination intelligence”
Claim 19: “non-transitory computer-readable medium”, “database”
Claim 20: “non-transitory computer-readable medium”, “global policy intelligence”, “receiving a message from an external medical institution”, “transmitting the global policy intelligence to the external medical institution when the message is the synchronization message”, “updating the global policy intelligence using a policy intelligence of the external medical institution provided from the external medical institution when the message is a federation message”
Claim 21: “apparatus”, “mixed distribution model”, “local policy intelligence reinforcement learning module”
Claim 22: “apparatus”, “electronic”, “local policy intelligence reinforcement learning module”
Claim 23: “mixed probability distribution model”, “reinforcement learning”
These features are additional elements that are recited at a high level of generality (e.g., the “A non-transitory computer-readable medium comprising a program code that, when executed by a processor, causes the processor to execute operations” performs no more than a statement that said instructions are executed) such that they amount to no more than mere instruction to apply the exception using generic computer components. See: MPEP 2106.05(f).
The additional elements are merely incidental or token additions to the claim that do not alter or affect how the process steps or functions in the abstract idea are performed (e.g., the “A non-transitory computer-readable medium comprising a program code that, when executed by a processor, causes the processor to execute operations” language is incidental to what instructions are executed). Therefore, the claimed additional elements do not add meaningful limitations to the indicated claims beyond a general linking to a technological environment. See: MPEP 2106.05(h).
The combination of these additional elements is no more than mere instructions to apply the exception using generic computer components. 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.
Hence, the 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. Accordingly, the claims are directed to an abstract idea (Step 2A Prong Two: NO).
Step 2B
The claims do 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, using the additional elements to perform the abstract idea amounts to no more than mere instructions to apply the exception using generic components. Mere instructions to apply an exception using a generic components cannot provide an inventive concept. See MPEP 2106.05(f).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are not integrated into the claim because they are merely incidental or token additions to the claim that do not alter or affect how the process steps or functions in the abstract idea are performed. Therefore, the claimed additional elements do not add meaningful limitations to the indicated claims beyond a general linking to a technological environment. See: MPEP 2106.05(h).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are configured to perform well-understood, routine, and conventional activities previously known to the industry. See: MPEP 2106.05(d). Said additional elements are recited at a high level of generality and provide conventional functions that do not add meaningful limits to practicing the abstract idea. The published specification supports this conclusion as follows:
[0026] Components that are described in the detailed description with reference to the terms "unit", "module", "block", "-er or -or", etc. and function blocks illustrated in drawings will be implemented with software, hardware, or a combination thereof. For example, the software may be a machine code, firmware, an embedded code, and application software. For example, the hardware may include an electrical circuit, an electronic circuit, a processor, a computer, an integrated circuit, integrated circuit cores, a pressure sensor, an inertial sensor, a microelectromechanical system (MEMS), a passive element, or a combination thereof.
[0041] For example, functions of the artificial intelligence apparatus 100 may be implemented using hardware including combined logic, sequential logic, one or more timers, counters, registers, and/or state machines, complex instruction set computer (C SIC) processors such as one or more complex programmable logic device (CPLD), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), and x86 processors and/or a central processing unit (CPU) such as a reduced instruction set computer (RISC) such as ARM processors, a graphics processing unit (GPU), a neural processing unit (NPU), a tensor processing unit (TPU), an accelerated processing unit (APU), etc. or a combination thereof, to execute instructions stored in any type of memory (e.g., a NAND flash memory, a flash memory such as a low-latency NAND flash memory, a persistent memory (PMEM) such as a cross-grid nonvolatile memory, a memory with mass resistance change, a phase change memory (PCM), etc. or a combination thereof), software, or a combination thereof.
[0050] In addition, according to embodiments, the above described operations of the artificial intelligence apparatus 100 may be implemented with program codes stored in a non-transitory computer-readable medium. For example, the non-transitory computer-readable media may include magnetic media, optical media, or combinations thereof ( e.g., a CD-ROM, a hard drive, a read-only memory, a flash drive, etc.).
Viewing the limitations as an ordered combination, the claims simply instruct the additional elements to implement the concept described above in the identification of abstract idea with routine, conventional activity specified at a high level of generality in a particular technological environment.
Hence, the claims as a whole, considering the additional elements individually and as an ordered combination, do not amount to significantly more than the abstract idea (Step 2B: NO).
Dependent claim(s) 4 – 6, 8 - 13, and 16 – 23 when analyzed as a whole, considering the additional elements individually and/or as an ordered combination, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea without significantly more. These claims fail to remedy the deficiencies of their parent claims above, and are therefore rejected for at least the same rationale as applied to their parent claims above, and incorporated herein.
Claim Rejections - 35 USC § 103
The rejection of Claim(s) 1 – 4, 7, 9 – 10, 14, and 16 – 17 under 35 U.S.C. 103 as being unpatentable over Laster et al., herein after Laster (U.S. Patent Number 11,322,250 B1) in view of Yoo et al., herein after Yoo (U.S. Publication Number 2022/0199258 A1) further in view of Saripalli et al., herein after Saripalli (U.S. Publication Number 2020/0337648 A1) were withdrawn in the Office Action mailed May 28, 2025.
The rejection of Claim(s) 5 – 6, 8, 11 – 13, 15, and 18 – 20 under 35 U.S.C. 103 as being unpatentable over Laster et al., herein after Laster (U.S. Patent Number 11,322,250 B1) in view of Yoo et al., herein after Yoo (U.S. Publication Number 2022/0199258 A1) further in view of Saripalli et al., herein after Saripalli (U.S. Publication Number 2020/0337648 A1) and Farh et al., herein after Farh (U.S. Publication Number 2018/0060523 A1) were withdrawn in the Office Action mailed May 28, 2025.
Response to Arguments
Applicant's arguments filed February 15, 2026 have been fully considered but they are not persuasive. The Applicant’s arguments have been addressed in the order in which they were presented.
Claim Rejections under 35 USC § 101
The Applicant argues the Examiner has not met the preponderance standard and has oversimplified the claim, specifically, the Applicant states the ordered combination of the claims as a whole define a specific AI system architecture. The Examiner respectfully disagrees. The limitation “a patient condition predictive intelligence deep learning module configured to train a patient condition predictive intelligence for predicting a following condition of the patient after applying the treatment method to the patient” discloses predicting a condition of a patient after applying a treatment method. The trained patient condition predictive intelligence and other learning modules recited in the claims are used to apply the abstract idea, and is described at a high level. These limitations fail to recite how the artificial intelligence is training the data. Thus, Applicant’s argument is not persuasive, and the rejection is maintained.
The Applicant argues the claimed operations cannot be performed in the human mind, specifically the Applicant states the claims recite computational processes that cannot reasonably be characterized as mental processes or as organizing human activity. The Examiner respectfully disagrees. Under its broadest reasonable interpretation, the Applicant’s claims are an abstract idea that falls into the grouping of “Certain Methods of Organizing Human Activity” which covers fundamental economic principles or practices, commercial or legal interactions, or managing personal behavior or relationships or interactions between people. The Examiner respectfully submits that the PEG (Patent Eligibility Guidelines) of January 2019 recite that “Certain Methods of Organizing Human Activity” include managing personal behavior or relationships or interactions between people, including social activities, teaching, and following rules or instructions. The present claims recite the abstract idea of determining a series of treatment paths that ultimately improve a patient to the best condition. The present claims recite receiving a medical record of a patient and converting the received medical record into an episode list including a condition of the patient, a treatment method, and a treatment history; separate the received medical record associated with the patient into an examination record table and a treatment record table; arrange the examination record table and the treatment record table in chronological order; replace missing values in the examination record table with one of an average value, a mode value and an interpolation value of multiple time series values between treatment orders of medical record items corresponding to the missing values; and convert the received medical record into the episode list based on the examination record table and the treatment record table, wherein the episode list is a time series having an order of a first condition of the patient, the treatment method applied to the patient, a second condition of the patient after applying the treatment method, and the treatment history of the patient; and wherein the patient condition is a time series mixed probability distribution model that predicts a plurality of conditions that can be resulted in when the treatment method is applied to the patient and a probability that each of the plurality of conditions can be resulted in. These features describe interactions with people, thus “Certain Methods of Organizing Human Activity”. Thus, if a claim limitation, under its broadest reasonable interpretation, covers interactions with people, but for the recitation of generic components, then it is still in the “Certain Methods of Organizing Human Activity” grouping.
The Applicant argues the claims provide technical solutions to technical problems, specifically the Applicant states the present claims address identified technical problems through specific AI architectures. The Examiner respectfully disagrees. The Examiner submits the Applicant’s argument has been addressed in the response above, and incorporated herein.
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 nonprovisional extension fee (37 CFR 1.17(a)) 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KRISTINE K RAPILLO whose telephone number is (571)270-3325. The examiner can normally be reached Monday - Friday 7:30 - 4 pm.
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/K.K.R/Examiner, Art Unit 3682
/ROBERT A SOREY/Primary Examiner, Art Unit 3682
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