{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T03:56:07Z","timestamp":1777348567391,"version":"3.51.4"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000092","name":"National Library of Medicine","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000092","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01LM013362"],"award-info":[{"award-number":["R01LM013362"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,11,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The lack of diversity, equity, and inclusion continues to hamper the artificial intelligence (AI) field and is especially problematic for healthcare applications. In this article, we expand on the need for diversity, equity, and inclusion, specifically focusing on the composition of AI teams. We call to action leaders at all levels to make team inclusivity and diversity the centerpieces of AI development, not the afterthought. These recommendations take into consideration mitigation at several levels, including outreach programs at the local level, diversity statements at the academic level, and regulatory steps at the federal level.<\/jats:p>","DOI":"10.1093\/jamia\/ocac156","type":"journal-article","created":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T15:09:50Z","timestamp":1662044990000},"page":"2178-2181","source":"Crossref","is-referenced-by-count":22,"title":["Picture a data scientist: a call to action for increasing diversity, equity, and inclusion in the age of AI"],"prefix":"10.1093","volume":"29","author":[{"given":"Anne A H","family":"de Hond","sequence":"first","affiliation":[{"name":"Clinical AI Implementation and Research Lab, Leiden University Medical Center , Leiden, The Netherlands"},{"name":"Department of Medicine (Biomedical Informatics), Stanford University , Stanford, California, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marieke M","family":"van Buchem","sequence":"additional","affiliation":[{"name":"Clinical AI Implementation and Research Lab, Leiden University Medical Center , Leiden, The Netherlands"},{"name":"Department of Medicine (Biomedical Informatics), Stanford University , Stanford, California, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tina","family":"Hernandez-Boussard","sequence":"additional","affiliation":[{"name":"Department of Medicine (Biomedical Informatics), Stanford University , Stanford, California, USA"},{"name":"Department of Biomedical Data Science, Stanford University , Stanford, California, USA"},{"name":"Department of Epidemiology & Population Health (By Courtesy), Stanford University , Stanford, California, 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