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Med."],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Health equity is a primary goal of healthcare stakeholders: patients and their advocacy groups, clinicians, other providers and their professional societies, bioethicists, payors and value based care organizations, regulatory agencies, legislators, and creators of artificial intelligence\/machine learning (AI\/ML)-enabled medical devices. Lack of equitable access to diagnosis and treatment may be improved through new digital health technologies, especially AI\/ML, but these may also exacerbate disparities, depending on how bias is addressed. We propose an expanded Total Product Lifecycle (TPLC) framework for healthcare AI\/ML, describing the sources and impacts of undesirable bias in AI\/ML systems in each phase, how these can be analyzed using appropriate metrics, and how they can be potentially mitigated. The goal of these \u201cConsiderations\u201d is to educate stakeholders on how potential AI\/ML bias may impact healthcare outcomes and how to identify and mitigate inequities; to initiate a discussion between stakeholders on these issues, in order to ensure health equity along the expanded AI\/ML TPLC framework, and ultimately, better health outcomes for all.<\/jats:p>","DOI":"10.1038\/s41746-023-00913-9","type":"journal-article","created":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T14:02:52Z","timestamp":1694527372000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":261,"title":["Considerations for addressing bias in artificial intelligence for health equity"],"prefix":"10.1038","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3490-0037","authenticated-orcid":false,"given":"Michael D.","family":"Abr\u00e0moff","sequence":"first","affiliation":[]},{"given":"Michelle E.","family":"Tarver","sequence":"additional","affiliation":[]},{"given":"Nilsa","family":"Loyo-Berrios","sequence":"additional","affiliation":[]},{"given":"Sylvia","family":"Trujillo","sequence":"additional","affiliation":[]},{"given":"Danton","family":"Char","sequence":"additional","affiliation":[]},{"given":"Ziad","family":"Obermeyer","sequence":"additional","affiliation":[]},{"given":"Malvina B.","family":"Eydelman","sequence":"additional","affiliation":[]},{"name":"Foundational Principles of Ophthalmic Imaging and Algorithmic Interpretation Working Group of the Collaborative Community for Ophthalmic Imaging Foundation, Washington, D.C.","sequence":"additional","affiliation":[]},{"given":"William H.","family":"Maisel","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,9,12]]},"reference":[{"key":"913_CR1","unstructured":"U.S. Department of Health and Human Services HRaSA, Office of Health Equity. 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Z.O. reports the following conflicts of interest: Chief Scientific Officer, Dandelion Health. None of the other authors report conflicts of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"170"}}