{"paper_id":"49aa3f9c-a4e2-41df-b3bc-2ba8daed3445","body_text":"Bibliometric Review of the Ethical and Legal Perspectives of Explainable Artificial Intelligence in Health | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Bibliometric Review of the Ethical and Legal Perspectives of Explainable Artificial Intelligence in Health Juan Morysson Viana Marciano, Vinicius Ponte Machado, Arlino Henrique Magalhães de Araújo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9448591/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Explainable Artificial Intelligence (XAI) has gained significant attention in healthcare due to the growing need for transparency, accountability, and trust in automated medical decision-making. Although the literature on XAI is expanding rapidly, especially in technical applications, there remains a gap in comprehensive assessments that address its ethical and legal implications in health-related contexts. This study presents a bibliometric review of the scientific production on XAI in healthcare, with a particular emphasis on ethical and legal perspectives. Using the Web of Science Core Collection and the Biblioshiny platform, 872 articles published between 2010 and 2025 were analyzed. The review maps annual publication trends, influential authors, prominent institutions, geographic distribution, and keyword patterns. The results reveal moderate growth in publications starting in 2019, and exponential growth by 2025, and highlight three main conceptual clusters: clinical applications and diagnostic imaging, technical foundations whit XAI e deep learning, and algorithmic governance. This is the first bibliometric analysis to explicitly address the intersection of explainability, ethics, and regulation in the context of medical AI, offering both a quantitative overview and a qualitative synthesis of this evolving interdisciplinary field. Explainable Artificial Intelligence (XAI) Medical AI Ethics in AI Legal Frameworks Transparency Bibliometric Analysis Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-9448591\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":625271392,\"identity\":\"65e07a39-7d41-479e-9e9a-2f45d552daa2\",\"order_by\":0,\"name\":\"Juan Morysson Viana Marciano\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIiWNgGAWjYBACxgYUboUEPwMzkOZhYEggUssZCckGQlrQDGhjkASbgU8L84zkZw8Yc2zyDc4ff/i4cJ6FhDk7A+ODt20MeeYN2LUwzkgzN2Dclma54UaOsfHMbRISls0MzIZz2xiKZQ7g0pJgJsG47bCBwQ0eNmnebRJ1BocZgIw2hsQZuFw/I/0bRMv548+keedISAC1sP/GryUHasuBBDNp3gawFjZmvFp63pRJJG5LM5AE+YXnGMgvjM2Sc85JFEvg0GLYnr5N4uM2GwM+UIjx1NRJmPMfPvjhTZlNHk4tDQyQKFA4ABUxgEQvLg0MDPJwRgNcyygYBaNgFIwCVAAAJnFRwjCrE58AAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"Instituto Federal do Piauí\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Juan\",\"middleName\":\"Morysson Viana\",\"lastName\":\"Marciano\",\"suffix\":\"\"},{\"id\":625271393,\"identity\":\"1d271789-c1d4-45dc-af4f-2df0bb2fc455\",\"order_by\":1,\"name\":\"Vinicius Ponte Machado\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Federal University of Piauí\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Vinicius\",\"middleName\":\"Ponte\",\"lastName\":\"Machado\",\"suffix\":\"\"},{\"id\":625271394,\"identity\":\"5b520084-e752-4a25-baf4-606bb68530fc\",\"order_by\":2,\"name\":\"Arlino Henrique Magalhães de Araújo\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Federal University of Piauí\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Arlino\",\"middleName\":\"Henrique Magalhães\",\"lastName\":\"de Araújo\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2026-04-17 11:38:28\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-9448591/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-9448591/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":108006990,\"identity\":\"53ab5cb3-178f-40a7-be01-1d111869a20b\",\"added_by\":\"auto\",\"created_at\":\"2026-04-28 12:58:07\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1187088,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"ExplainableArtificialIntelligenceinHealthcareABibliometricReviewonEthicalandLegalPerspectives2.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9448591/v1_covered_d795f49b-fad8-4c51-b240-b168f0b85f54.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Bibliometric Review of the Ethical and Legal Perspectives of Explainable Artificial Intelligence in Health\",\"fulltext\":[],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":false,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":true,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":true,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":true,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Explainable Artificial Intelligence (XAI), Medical AI, Ethics in AI, Legal Frameworks, Transparency, Bibliometric Analysis\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-9448591/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-9448591/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"Explainable Artificial Intelligence (XAI) has gained significant attention in healthcare due to the growing need for transparency, accountability, and trust in automated medical decision-making. 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