ArticleOman medical journal2026
Knowledge, Attitude, and Perception of Artificial Intelligence in Healthcare Among Postgraduate Residents: A Cross-sectional Survey.
Article in Oman medical journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
Objectives: Artificial intelligence (AI) is increasingly integrated into healthcare, enhancing diagnosis, treatment planning, and medical education. However, there is limited research on postgraduate residents' knowledge, attitudes, and perceptions of AI, particularly in Oman. Assessing their familiarity with AI is essential for effective curriculum development and clinical integration. This study sought to evaluate the knowledge, attitudes, and perceptions of AI among postgraduate medical residents in Oman and to identify gaps and potential areas for educational improvement. Methods: A cross-sectional survey was conducted at the Oman Medical Specialty Board in Muscat, Oman, from September to December 2024. A digital, self-administered questionnaire assessed residents' familiarity with AI concepts, attitudes toward its role in medicine, and perceptions of its impact on clinical practice and medical education. Data were analyzed using descriptive and inferential statistics. Results: A total of 256 residents participated (response rate = 33.3%). While 70.7% reported familiarity with AI, only 35.5% felt that their training had adequately prepared them to work alongside AI. Most residents (80.1%) supported integrating AI education into medical curricula, with 74.6% recommending its introduction at the undergraduate level. Concerns included AI's potential impact on job security (44.1%) and ethical challenges (89.1%). AI knowledge was significantly associated with sex ( Conclusions: Significant gaps exist in AI knowledge among medical residents, despite widespread support for AI integration into medical education. Structured AI training and continuous feedback systems are essential to enhance AI literacy and ensure its effective application in clinical practice.
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