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All Journal International Journal of Advanced Multidisciplinary
Ikhsan Nurahman
Yarsi Pratama University, Banten, Indonesia
Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences

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Ethical and Regulatory Evaluation of Artificial Intelligence in Clinical Radiology Practice Evie Kusmiati; Intan Masita Hayati; Syahroni Lubis; Ikhsan Nurahman; Dede Cahyadi; Mustain Billah Marap
International Journal of Advanced Multidisciplinary Vol. 4 No. 3 (2025): International Journal of Advanced Multidisciplinary (October - December 2025)
Publisher : Greenation Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/ijam.v4i3.1389

Abstract

The use of artificial intelligence (AI) in clinical radiology has grown rapidly in line with digital transformation and the increasing demand for efficiency in healthcare services. However, the rapid adoption of AI has not always been accompanied by adequate ethical and regulatory readiness. This study aims to evaluate the ethical framework and regulatory governance of AI applications in radiology practice, both globally and nationally, through a systematic literature review with a narrative analysis approach. The findings reveal that international bodies such as the WHO, FDA, and the European Union have developed ethical guidelines and algorithm audit standards emphasizing transparency, accountability, and patient data security. In contrast, Indonesia has yet to establish specific regulations addressing certification, legal responsibility, and data privacy in medical AI applications. Major challenges include low digital literacy among healthcare professionals, overlapping institutional authorities, and the absence of independent oversight mechanisms. Therefore, the establishment of a national ethical framework, algorithm audit system, and professional training policies is essential to ensure that AI utilization in clinical radiology is conducted safely, transparently, and equitably.
Co-Authors Dede Cahyadi Evie Kusmiati Intan Masita Hayati Mustain Billah Marap Syahroni Lubis