ArticleMedicine2026
Physician readiness for artificial intelligence integration in clinical screening and diagnosis: Multicenter cross-sectional study in Jeddah, Saudi Arabia.
Article in Medicine, 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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14 authors.
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Abstract
Artificial intelligence (AI) is increasingly incorporated into clinical screening and diagnostic workflows worldwide. However, the effectiveness and safety of AI implementation depend largely on physicians' readiness, including their knowledge, attitudes, and perceived barriers. In Saudi Arabia, where healthcare digital transformation is a strategic priority under Vision 2030, evidence regarding physician preparedness for AI-enabled clinical practice remains limited. A multicenter cross-sectional study was conducted among physicians and medical interns working in governmental and private hospitals in Jeddah, Saudi Arabia, between February and April 2025. Data were collected using a validated, self-administered questionnaire assessing demographic characteristics, knowledge, attitudes, and perceived barriers related to AI use in clinical screening and diagnosis. Descriptive statistics, chi-square tests, and multivariate logistic regression analyses were performed using International Business Machines Statistical Package for the Social Sciences version 26. A total of 435 physicians participated in the study. Although most respondents reported positive attitudes toward AI integration in clinical practice (83.7%), only half demonstrated good knowledge of AI concepts and applications (50.3%), indicating a clear readiness gap. Radiology (75.9%) and pathology (43.7%) were identified as the clinical areas with the greatest perceived potential for AI implementation. The most frequently reported barriers were insufficient training (58.9%) and lack of trust in AI systems (53.8%). In multivariate analysis, non-Saudi physicians were significantly more likely to exhibit positive attitudes toward AI adoption (adjusted odds ratio = 1.75, P = .047). Despite strong physician enthusiasm for AI, substantial gaps in knowledge and training persist, posing challenges to effective implementation in clinical practice. Addressing physician readiness through structured educational programs, trust-building strategies, and clear regulatory frameworks is essential to ensure safe, sustainable, and effective integration of AI into Saudi healthcare systems.
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