An Intentional and Ethical Integration of AI In Medical Imaging.
This article focuses on the intentional and ethical integration of artificial intelligence (AI) in medical imaging, emphasizing the evolving role of radiologic technologists as supervisors and ethical stewards of AI technologies. It outlines AI’s capabilities in enhancing diagnostic accuracy, workfl...
| Publicado en: | Radiologic Technology Vol. 97; no. 5; pp. 355 - 364 |
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| Autor principal: | |
| Formato: | CEU Journal Article |
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American Society of Radiologic Technologists
May/Jun2026
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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=195527048&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 195527048 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00338397 39J jtl: Radiologic Technology issn: 00338397 maglogo: N pubinfo: dt: May/Jun2026 vid: 97 iid: 5 pid: 7052 pub: American Society of Radiologic Technologists place: Alburquerque, New Mexico artinfo: ui: 195527048 195527048 195527048 195527048 ppf: 355 ppct: 9 formats: fmt: @attributes: type: P tig: atl: An Intentional and Ethical Integration of AI In Medical Imaging. aug: au: Turpin, Dean affil: Program chair of radiologic technology in the College of Health and Public Administration at Franklin University in Columbus, Ohio sug: subj: Artificial Intelligence Ethical Issues Artificial Intelligence Utilization Diagnostic Imaging Methods Technology, Radiologic Education, Radiologic Technology Quality Assurance Ethics Education, Continuing (Credit) Decision Support Systems, Clinical Utilization Patient Safety Attitude of Health Personnel Education, Continuing Professional Competence Medical Informatics ab: This article focuses on the intentional and ethical integration of artificial intelligence (AI) in medical imaging, emphasizing the evolving role of radiologic technologists as supervisors and ethical stewards of AI technologies. It outlines AI’s capabilities in enhancing diagnostic accuracy, workflow efficiency, quality assurance, and personalized patient care, while highlighting challenges related to clinical autonomy, ethical implementation, bias, patient consent, and cultural considerations. The report advocates for comprehensive education, transparent governance, and human-centered AI design to ensure that AI supports rather than replaces human judgment and compassion in health care. It also envisions future AI applications that augment radiologic practice through real-time protocol recommendations, multilingual communication, and continuous quality improvement, stressing the importance of maintaining professional accountability and patient dignity throughout AI adoption. pubtype: Academic Journal doctype: CEU Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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