Medical Clinical Minds Meet Artificial Intelligence: Italian Physicians’ Knowledge, Attitudes, and Concordance between Italian Physicians and AI-Generated Diagnoses. A National Cross-Sectional Study

Abstract

Abstract Background Artificial Intelligence has increasingly been integrated into clinical practice, yet its adoption and perception among medical professionals remain poorly understood, particularly in the Italian healthcare system. To investigate Italian physicians’ knowledge, attitudes, and clinical concordance with AI-generated diagnostic recommendations, using a validated questionnaire and a clinical scenario processed by ChatGPT. Methods A national, cross-sectional web-based survey was conducted among 587 Italian physicians using an online validated questionnaire. The first part of the questionnaire assessed self-reported knowledge, prior experience, attitudes, and willingness to adopt AI in medicine. The second part assessed clinical concordance between AI proposals and physicians about clinical cases evaluated by ChatGPT. Results Most participants reported basic AI knowledge (n=380, 64.8%) and minimal exposure to AI training (18.4%). Only 21.6% reported they used AI in clinical practice, and the most familiar application was diagnostic imaging (35.4% of AI users; 7.7% of the total sample). Major perceived barriers included lack of training (76.7%) and resistance to change (50.9%). In the universal clinical scenario, physicians showed the highest agreement with ChatGPT’s correct diagnosis (mean=4.07) compared to incorrect alternatives (mean=2.57 and 1.82, p<0.001). For correct diagnosis, the agreement rate was very high at 89% [86%-91%]. Conclusions Italian physicians showed a strong interest in adopting AI tools, despite significant knowledge gaps and limited practical experience. The high concordance between physicians’ evaluations and ChatGPT’s diagnostic insights suggests potential for AI-based decision support in clinical workflows. Targeted training and institutional support are essential to bridge the gap between enthusiasm and readiness for AI integration.

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