{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T17:17:15Z","timestamp":1778692635793,"version":"3.51.4"},"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>Addressing algorithmic bias in healthcare is crucial for ensuring equity in patient outcomes, particularly in cross-institutional collaborations where privacy constraints often limit data sharing. Federated learning (FL) offers a solution by enabling institutions to collaboratively train models without sharing sensitive data, but challenges related to fairness remain. To tackle this, we propose Fair Federated Machine Learning (FairFML), a model-agnostic framework designed to reduce algorithmic disparities while preserving patient privacy. Validated in a real-world study on gender disparities in cardiac arrest outcomes, FairFML improved fairness by up to 65% compared to centralized models, without compromising predictive performance.<\/jats:p>","DOI":"10.3233\/shti251245","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:45:51Z","timestamp":1754567151000},"source":"Crossref","is-referenced-by-count":1,"title":["FairFML: A Unified Approach to Algorithmic Fair Federated Learning with Applications to Reducing Gender Disparities in Cardiac Arrest Outcomes"],"prefix":"10.3233","author":[{"given":"Siqi","family":"Li","sequence":"first","affiliation":[{"name":"Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0845-9524","authenticated-orcid":false,"given":"Qiming","family":"Wu","sequence":"additional","affiliation":[{"name":"Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8659-5425","authenticated-orcid":false,"given":"Xin","family":"Li","sequence":"additional","affiliation":[{"name":"Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5381-9198","authenticated-orcid":false,"given":"Di","family":"Miao","sequence":"additional","affiliation":[{"name":"Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7056-9559","authenticated-orcid":false,"given":"Chuan","family":"Hong","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9811-1725","authenticated-orcid":false,"given":"Wenjun","family":"Gu","sequence":"additional","affiliation":[{"name":"Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6758-4472","authenticated-orcid":false,"given":"Yilin","family":"Ning","sequence":"additional","affiliation":[{"name":"Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3249-4869","authenticated-orcid":false,"given":"Yuqing","family":"Shang","sequence":"additional","affiliation":[{"name":"Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3610-4883","authenticated-orcid":false,"given":"Nan","family":"Liu","sequence":"additional","affiliation":[{"name":"Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore"}]}],"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\/SHTI251245","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:45:52Z","timestamp":1754567152000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI251245"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti251245","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]]}}}