# US 2024/0203545 A1 · Artificial intelligence medical examination and medical record generation system and method thereof > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2024/0203545 A1 - Document ID: US20240203545A1 - Status: Published application - Kind: A1 - Application number: 18/203,795 - Filed: 2023-05-31 - Published: 2024-06-20 - Earliest claimed: 2022-12-19 - Assignees: BePlus Healthcare Inc. - Applicants: BePlus Healthcare Inc. - Inventors: Hoon Jae CHUNG; Ki Joon HUGH; Jae Young KIM; Jee Hong KIM; Woo Taek LIM - Web page: https://patentgrep.com/patent/US20240203545A1 ## CPC - G16H 10/60: for patient-specific data, e.g. for electronic patient records - G16H 10/20: for electronic clinical trials or questionnaires - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract An artificial intelligence medical examination and medical record generation system includes a medical examination database storing a medical examination item and a past medical examination result, a medical examination generation unit generating or updating a medical examination scenario by selecting a medical examination item through a medical examination-generation artificial intelligence based on patient data, a medical examination provision unit providing the medical examination scenario with an expression familiar to a patient through natural language processing of a medical examination-provision artificial intelligence based on the patient data, a medical examination analysis unit analyzing a patient answer to the medical examination scenario through structuralizing, standardizing, and encoding processes, a record generation unit generating a medical record familiar to medical personnel based on an analysis result generated by the medical examination analysis unit, and a transmission unit transmitting the medical record to the medical personnel and an electronic medical record system. ## Claims ### Claim 1 An artificial intelligence medical examination and medical record generation system, the system comprising: a medical examination database (DB) storing a medical examination item and a past medical examination result; a medical examination generation unit configured for generating or updating a medical examination scenario by selecting an appropriate medical examination item through a medical examination-generation artificial intelligence based on patient data; a medical examination provision unit configured for processing and providing the medical examination scenario with an expression familiar to a patient through natural language processing of a medical examination-provision artificial intelligence based on the patient data; a medical examination analysis unit configured for analyzing a patient answer to the medical examination scenario through structuralizing, standardizing, and encoding processes; a record generation unit configured for generating a medical record familiar to medical personnel based on an analysis result generated by the medical examination analysis unit; and a transmission unit configured for transmitting the medical record to the medical personnel and an electronic medical record (EMR) system. ### Claim 2 (depends on 1) The system of claim 1, wherein the medical examination analysis unit includes: a structurer configured for classifying the answer to the medical examination item into an item or attribute necessary for a diagnosis based on its meaning; a standardizer configured for replacing the classified item and attribute with a standard word or sentence having the same meaning in standard terminology using Korean standard terminology of medicine (KOSTOM) or systematized nomenclature of medicine clinical terms (SNOMED-CT); and an encoder configured for assigning a code corresponding to the standard terminology to the standard word or sentence. ### Claim 3 (depends on 1) The system of claim 1, wherein the medical examination generation unit is configured to generate the medical examination scenario by selecting the appropriate medical examination item among the stored medical examination items based on the patient data and a patient symptom. ### Claim 4 (depends on 1) The system of claim 1, wherein the patient data includes data on a past treatment history of the patient, and one or more of age, gender, usage language, education level, past treatment history, residential area, lifestyle, or allergy data, input by the patient before medical examination is generated, and the medical examination generation unit is configured to update the medical examination item in consideration of a corrected content when the patient data or data acquired by structuralizing an existing medical examination item and an answer to the medical examination item is corrected. ### Claim 5 (depends on 1) The system of claim 1, wherein the medical examination generation unit is configured to generate the updated medical examination scenario by selecting an additionally-necessary medical examination item based on the analysis result generated by the medical examination analysis unit when the patient inputs the answer to the medical examination scenario. ### Claim 6 (depends on 1) The system of claim 1, wherein the medical examination provision unit is configured to convert an expression in the medical examination scenario into a familiar expression that is easy for the patient to understand through the natural language processing based on the patient data. ### Claim 7 (depends on 1) The system of claim 1, wherein the record generation unit is configured to generate the medical record by converting the patient answer to the medical examination scenario into an expression that is easy for the medical personnel to understand based on the analysis performed by the medical examination analysis unit. ### Claim 8 (depends on 1) The system of claim 1, wherein the transmission unit is configured to directly transmits the medical record to a medical personnel terminal or to an EMR server of the linked EMR system to which the medical personnel have access rights. ### Claim 9 An artificial intelligence medical examination and medical record generation method, the method comprising: analyzing data of a patient who wants to use an artificial intelligence medical examination and medical record generation system; generating a medical examination scenario by selecting a medical examination item corresponding to the patient data; reconfiguring the medical examination scenario into an expression corresponding to the patient data and providing the expression to the patient; systematizing and analyzing an answer to the medical examination scenario that is received from the patient; generating a medical record for the patient based on an analysis result of the answer to the medical examination scenario; and transmitting the medical record to a medical personnel terminal or a linked electronic medical record (EMR) server. ### Claim 10 (depends on 9) The method of claim 9, wherein the patient data includes data on a past treatment history of the patient, and one or more of age, gender, usage language, education level, past treatment history, residential area, lifestyle, or allergy data, and in the generating of the medical examination scenario, the medical examination item is corrected or updated in consideration of a corrected content when the patient data or data acquired by structuralizing an existing medical examination item and an answer to the existing medical examination item is corrected. ### Claim 11 (depends on 9) The method of claim 9, wherein, in the generating of the medical examination scenario, the updated medical examination scenario is generated by selecting an additionally-necessary medical examination item by accepting feedback based on the analysis result from the medical examination analysis unit when the patient inputs the answer to the generated medical examination scenario. ### Claim 12 (depends on 9) The method of claim 9, wherein, in the reconfiguring of the medical examination scenario, the expression in each medical examination item is converted into a more familiar expression that is easier for the patient to understand by reflecting one or more of data such as age, usage language, education level, and residential area among the patient data through natural language processing of an artificial intelligence. ### Claim 13 (depends on 9) The method of claim 9, wherein the systematizing and analyzing of the answer comprises: classifying the patient answer to the medical examination into an item or attribute necessary for a diagnosis based on its meaning; replacing the classified item and attribute with a standard word or sentence having the same meaning in standard terminology using Korean standard terminology of medicine (KOSTOM) or systematized nomenclature of medicine clinical terms (SNOMED-CT); and assigning a code corresponding to the standard terminology to the standard word or sentence. ### Claim 14 (depends on 9) The method of claim 9, wherein, in the generating of the medical record, the medical record is generated by reconfiguring medical examination result data acquired by analyzing the answer to the medical examination scenario that is input by the patient based on a medical term.