{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:03:45Z","timestamp":1755219825059,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"electronic","value":"9781643686080"}],"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>Clinical trial eligibility criteria, often presented as complex free text, pose significant challenges for automated processing. This study introduces a Decomposition and Parsing (DP) workflow to address these challenges by systematically breaking down criteria into \u201cstudy traits\u201d\u2014the smallest meaningful units\u2014and structuring them with components such as entities, modifiers, constraints, and negations. Leveraging advanced large language models (LLMs) like GPT-4o and Llama3.3 with Chain-of-Thought prompting, the workflow successfully processes Alzheimer\u2019s disease trial datasets, achieving strong performance in tasks like logical relationship extraction and trait computability determination. However, challenges remain in capturing nuanced elements like modifiers. The study also proposes innovative evaluation metrics that outperform traditional approaches in assessing the quality of automated extractions. This scalable and intuitive framework advances the representation of clinical trial eligibility criteria, paving the way for improved biomedical informatics applications and highlighting the need for domain-specific fine-tuning and broader dataset integration.<\/jats:p>","DOI":"10.3233\/shti250928","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:35:28Z","timestamp":1754566528000},"source":"Crossref","is-referenced-by-count":0,"title":["Clinical Trial Eligibility Criteria Decomposition and Parsing with Large Language Models"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6259-0833","authenticated-orcid":false,"given":"Hongyu","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA"}]},{"given":"Lingfei","family":"Qian","sequence":"additional","affiliation":[{"name":"Section of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, CT, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0290-8058","authenticated-orcid":false,"given":"Xing","family":"He","sequence":"additional","affiliation":[{"name":"Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5100-3821","authenticated-orcid":false,"given":"Aokun","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7373-4716","authenticated-orcid":false,"given":"Yu","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA"}]},{"given":"Qinling","family":"Gou","sequence":"additional","affiliation":[{"name":"Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA"}]},{"given":"Yuxuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA"}]},{"given":"Yan","family":"Wang","sequence":"additional","affiliation":[{"name":"Section of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, CT, USA"}]},{"given":"Xuguang","family":"Ai","sequence":"additional","affiliation":[{"name":"Section of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, CT, USA"}]},{"given":"Yujia","family":"Zhou","sequence":"additional","affiliation":[{"name":"Section of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, CT, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5807-2635","authenticated-orcid":false,"given":"Inessa","family":"Cohen","sequence":"additional","affiliation":[{"name":"Section of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, CT, USA"}]},{"given":"Qingyu","family":"Chen","sequence":"additional","affiliation":[{"name":"Section of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, CT, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5274-4672","authenticated-orcid":false,"given":"Hua","family":"Xu","sequence":"additional","affiliation":[{"name":"Section of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, CT, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2238-5429","authenticated-orcid":false,"given":"Jiang","family":"Bian","sequence":"additional","affiliation":[{"name":"Biostatistics and Health Data Science, School of Medicine, Indiana University, Indianapolis, IN, USA"}]}],"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\/SHTI250928","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:35:28Z","timestamp":1754566528000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250928"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250928","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}