{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T02:27:25Z","timestamp":1772591245016,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686080","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,7]]},"abstract":"<jats:p>Current approaches lack efficient methods to convert diverse healthcare data formats into standardized Fast Healthcare Interoperability Resources (FHIR). LINK-FHIR is a novel system for converting diverse Electronic Health Records into FHIR-compliant resources. The system leverages fine-tuned Large Language Models through a unified pipeline to efficiently process unstructured clinical notes, semi-structured lab reports, and structured tables. LINK-FHIR features dual interfaces that offer automated machine-to-machine integration and an intuitive user interface for data visualization and management. The system offers flexible deployment options to ensure compliance with healthcare security and privacy regulations. Comprehensive evaluation demonstrates LINK-FHIR\u2019s robust performance across diverse data formats. LINK-FHIR has the potential to enhance Health Information Exchange interoperability significantly, operational efficiency across healthcare institutions.<\/jats:p>","DOI":"10.3233\/shti250793","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:31:17Z","timestamp":1754566277000},"source":"Crossref","is-referenced-by-count":1,"title":["LLM-Integrated Normalization and Knowledge for FHIR (LINK-FHIR)"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-4313-6133","authenticated-orcid":false,"given":"Zhen","family":"Hou","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering and Informatics"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3604-166X","authenticated-orcid":false,"given":"Ming","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Human-Centered Computing, Luddy School of Informatics, Computing, and Engineering, Indiana University, Indianapolis, IN"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1975-1272","authenticated-orcid":false,"given":"Hao","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computing, College of Science and Mathematics, Montclair State University, Montclair, NJ"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1245-7203","authenticated-orcid":false,"given":"Yan","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering and Informatics"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI250793","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:31:17Z","timestamp":1754566277000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250793"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250793","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}