Use of AI as a Research Recruitment Tool: A DSMB Perspective.
The article focuses on the implications of using artificial intelligence (AI) for participant recruitment in clinical trials from the perspective of data safety monitoring boards (DSMBs), also known as data safety monitoring committees (DSMCs). It highlights the potential benefits of AI in enhancing...
| Publicado en: | American Journal of Bioethics Vol. 26; no. 8; pp. 65 - 68 |
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| Formato: | commentary Journal Article |
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Taylor & Francis Ltd
Aug2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=195895374&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 195895374 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15265161 FKZ jtl: American Journal of Bioethics issn: 15265161 maglogo: N pubinfo: dt: Aug2026 vid: 26 iid: 8 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 195895374 195895374 195895374 10.1080/15265161.2026.2690925 195895374 ppf: 65 ppct: 3 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Use of AI as a Research Recruitment Tool: A DSMB Perspective. aug: au: Barnbaum, Deborah R. affil: Kent State University sug: subj: Artificial Intelligence Utilization Research Ethics Research Subject Recruitment Clinical Trials Patient Selection Bioethics Safety Accountability Artificial Intelligence Ethical Issues ab: The article focuses on the implications of using artificial intelligence (AI) for participant recruitment in clinical trials from the perspective of data safety monitoring boards (DSMBs), also known as data safety monitoring committees (DSMCs). It highlights the potential benefits of AI in enhancing recruitment efficiency, reducing bias, and improving trial completion rates, which align with DSMB goals of protecting participants and ensuring scientific integrity. However, the article emphasizes challenges related to AI’s explainability, reliability, and oversight, recommending that researchers maintain transparency about AI use and that DSMBs incorporate AI expertise to properly evaluate recruitment algorithms. It also notes potential difficulties in expanding DSMB membership due to limited AI experts and varying opinions on adding specialized members, while underscoring the importance of early integration of such expertise to safeguard participant welfare. pubtype: Academic Journal doctype: commentary Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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