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A Bilingual On-Premises AI Agent for Clinical Drafting: Implementation Report of Seamless Electronic Health Records Integration in the Y-KNOT Project

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dc.contributor.authorKim, Hanjae-
dc.contributor.authorLee, So-Yeon-
dc.contributor.authorYou, Seng Chan-
dc.contributor.authorHuh, Sookyung-
dc.contributor.authorKim, Jai-Eun-
dc.contributor.authorKim, Sung-Tae-
dc.contributor.authorKo, Dong-Ryul-
dc.contributor.authorKim, Ji Hoon-
dc.contributor.authorLee, Jae Hoon-
dc.contributor.authorLim, Joon Seok-
dc.contributor.authorPark, Moo Suk-
dc.contributor.authorLee, Kang Young-
dc.date.accessioned2026-01-16T07:53:42Z-
dc.date.available2026-01-16T07:53:42Z-
dc.date.created2026-01-09-
dc.date.issued2025-11-
dc.identifier.issn2291-9694-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/209839-
dc.description.abstractBackground: Large language models (LLMs) have shown promise in reducing clinical documentation burden, yet their real-world implementation remains rare. Especially in South Korea, hospitals face several unique challenges, such as strict data sovereignty requirements and operating in environments where English is not the primary language for documentation. Therefore, we initiated the Your-Knowledgeable Navigator of Treatment (Y-KNOT) project, aimed at developing an onpremises bilingual LLM-based artificial intelligence (AI) agent system integrated with electronic health records (EHRs) for Objective: We present the Y-KNOT project and provide insights into implementing AI-assisted clinical drafting tools within clinical co-development, and EHR integration. We developed a foundation LLM by pretraining Llama3-8B with Korean and tasks through iterative cycles that aligned physicians' clinical requirements, hospital data availability, documentation standImplementation (Results): The resulting system processes emergency department discharge summaries and preanesthetic assessments while maintaining existing clinical workflows. The drafting process is automatically triggered by specific events, such as scheduled batch jobs, with medical records automatically fed into the LLM as input. The agent is built on premises, locating all the architecture inside the hospital. Conclusions: The Y-KNOT project demonstrates the first seamless integration of an AI agent into an EHR system for clinical drafting. In collaboration with various clinical and administrative teams, we could promptly implement an LLM while addressing key challenges of data security, bilingual requirements, and workflow integration. Our experience highlights a practical and scalable approach to utilizing LLM-based AI agents for other health care institutions, paving the way for broader adoption of LLM-based solutions.-
dc.languageEnglish-
dc.publisherJMIR Publications-
dc.relation.isPartOfJMIR MEDICAL INFORMATICS-
dc.relation.isPartOfJMIR MEDICAL INFORMATICS-
dc.subject.MESHArtificial Intelligence*-
dc.subject.MESHDocumentation-
dc.subject.MESHElectronic Health Records*-
dc.subject.MESHHumans-
dc.subject.MESHMultilingualism*-
dc.subject.MESHRepublic of Korea-
dc.titleA Bilingual On-Premises AI Agent for Clinical Drafting: Implementation Report of Seamless Electronic Health Records Integration in the Y-KNOT Project-
dc.typeArticle-
dc.contributor.googleauthorKim, Hanjae-
dc.contributor.googleauthorLee, So-Yeon-
dc.contributor.googleauthorYou, Seng Chan-
dc.contributor.googleauthorHuh, Sookyung-
dc.contributor.googleauthorKim, Jai-Eun-
dc.contributor.googleauthorKim, Sung-Tae-
dc.contributor.googleauthorKo, Dong-Ryul-
dc.contributor.googleauthorKim, Ji Hoon-
dc.contributor.googleauthorLee, Jae Hoon-
dc.contributor.googleauthorLim, Joon Seok-
dc.contributor.googleauthorPark, Moo Suk-
dc.contributor.googleauthorLee, Kang Young-
dc.identifier.doi10.2196/76848-
dc.relation.journalcodeJ03664-
dc.identifier.eissn2291-9694-
dc.identifier.pmid41284981-
dc.subject.keywordartificial intelligence agent-
dc.subject.keywordlarge language models-
dc.subject.keyworddocumentation-
dc.subject.keywordelectronic health records-
dc.subject.keywordinsights-
dc.contributor.affiliatedAuthorKim, Hanjae-
dc.contributor.affiliatedAuthorYou, Seng Chan-
dc.contributor.affiliatedAuthorHuh, Sookyung-
dc.contributor.affiliatedAuthorKim, Ji Hoon-
dc.contributor.affiliatedAuthorLee, Jae Hoon-
dc.contributor.affiliatedAuthorLim, Joon Seok-
dc.contributor.affiliatedAuthorPark, Moo Suk-
dc.contributor.affiliatedAuthorLee, Kang Young-
dc.identifier.wosid001634505900002-
dc.citation.volume13-
dc.identifier.bibliographicCitationJMIR MEDICAL INFORMATICS, Vol.13, 2025-11-
dc.identifier.rimsid90838-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.journalClass1-
dc.subject.keywordAuthorartificial intelligence agent-
dc.subject.keywordAuthorlarge language models-
dc.subject.keywordAuthordocumentation-
dc.subject.keywordAuthorelectronic health records-
dc.subject.keywordAuthorinsights-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalWebOfScienceCategoryMedical Informatics-
dc.relation.journalResearchAreaMedical Informatics-
dc.identifier.articlenoe76848-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Emergency Medicine (응급의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Anesthesiology and Pain Medicine (마취통증의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers

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