{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:03:30Z","timestamp":1755219810670,"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>Background: Automated classification of medical literature is increasingly vital, especially in oncology. As shown in previous work, LLMs can be used as part of a flexible framework to accurately classify biomedical literature and trials. In the present study, we aimed to explore to what extent a consensus-based approach could improve classification performance. Methods: The three LLMs Mixtral-8x7B, Meta-Llama-3.1-70B, and Qwen2.5-72B were used to classify oncological trials across four data sets with nine questions. Metrics (accuracy, precision, recall, F1-score) were assessed for individual models and consensus results. Results: Consensus was achieved in 93.93% of cases, improving accuracy (98.34%), precision (97.01%), recall (98.11%), and F1-score (97.55%) over individual models. Conclusions: The consensus-based LLM framework delivers high accuracy and adaptability for classifying oncological trials, with potential applications in biomedical research and trial management.<\/jats:p>","DOI":"10.3233\/shti250837","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:32:40Z","timestamp":1754566360000},"source":"Crossref","is-referenced-by-count":0,"title":["Consensus Finding Among LLMs to Retrieve Information About Oncological Trials"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5374-8720","authenticated-orcid":false,"given":"Fabio","family":"Dennst\u00e4dt","sequence":"first","affiliation":[{"name":"Inselspital, Bern University Hospital and University of Bern, Switzerland"},{"name":"School of Medicine, University of St. Gallen, St. Gallen, Switzerland"}]},{"given":"Paul","family":"Windisch","sequence":"additional","affiliation":[{"name":"Cantonal Hospital Winterthur, Winterthur, Switzerland"}]},{"given":"Irina","family":"Filchenko","sequence":"additional","affiliation":[{"name":"Inselspital, Bern University Hospital and University of Bern, Switzerland"}]},{"given":"Johannes","family":"Zink","sequence":"additional","affiliation":[{"name":"Technical University of Munich, Heilbronn, Germany"}]},{"given":"Paul Martin","family":"Putora","sequence":"additional","affiliation":[{"name":"Inselspital, Bern University Hospital and University of Bern, Switzerland"},{"name":"Cantonal Hospital of St. Gallen, St. Gallen, Switzerland"}]},{"given":"Ahmed","family":"Shaheen","sequence":"additional","affiliation":[{"name":"Alexandria University, Faculty of Medicine, Alexandria, Egypt"}]},{"given":"Roberto","family":"Gaio","sequence":"additional","affiliation":[{"name":"Inselspital, Bern University Hospital and University of Bern, Switzerland"}]},{"given":"Nikola","family":"Cihoric","sequence":"additional","affiliation":[{"name":"Inselspital, Bern University Hospital and University of Bern, Switzerland"}]},{"given":"Marie","family":"Wosny","sequence":"additional","affiliation":[{"name":"School of Medicine, University of St. Gallen, St. Gallen, Switzerland"}]},{"given":"Stefanie","family":"Aeppli","sequence":"additional","affiliation":[{"name":"Cantonal Hospital of St. Gallen, St. Gallen, Switzerland"}]},{"given":"Max","family":"Schmerder","sequence":"additional","affiliation":[{"name":"Inselspital, Bern University Hospital and University of Bern, Switzerland"}]},{"given":"Mohamed","family":"Shelan","sequence":"additional","affiliation":[{"name":"Inselspital, Bern University Hospital and University of Bern, Switzerland"}]},{"given":"Janna","family":"Hastings","sequence":"additional","affiliation":[{"name":"School of Medicine, University of St. Gallen, St. Gallen, Switzerland"},{"name":"Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland"},{"name":"Swiss Institute of Bioinformatics, Lausanne, Switzerland"}]}],"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\/SHTI250837","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:32:40Z","timestamp":1754566360000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250837"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250837","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]]}}}