Evaluating the Effectiveness of an AI-Powered Clinical Training Program on Physicians’ Diagnostic Skills: A Quasi-Experimental Study | ||||
| ARCADEs of MEDICINE | ||||
| Articles in Press, Accepted Manuscript, Available Online from 19 July 2025 | ||||
| Document Type: Original Research | ||||
| DOI: 10.21608/arcmed.2025.372772.1108 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Ali Essam Ibrahim  
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| Medical education department | ||||
| Abstract | ||||
| Abstract Background: The rapid advancement of technology has completely altered teaching methods and learning styles; leading to transformation in the future of medicine. This study aimed to investigate the effectiveness of using an artificial intelligence (AI) model based on a medical educational framework in improving the diagnostic skills of clinicians. Methods: This quasi-experimental pre-posttest study was conducted at an Egyptian boarding medical school on 60 participants during the period from August 2022, to October 2023. Results: The training program resulted in significant improvement across all test metrics. For the MCQ (multiple choice questions), the training program elicited an increase in the median score in all 60 participants. Similarly, the median score of assessed diagnostic skills in all 60 participants increased. Looking at the total scores combining MCQ and rubric, the training program elicited an increase in the median score in all participants. There was a statistically significant increase in the median score from 13 to 32.5 with an increase rate of 21 (p < 0.001). Discussion: Fostering a collaborative mindset that promotes clinician participation in AI development is crucial for gaining acceptance and positioning tools as enhancing rather than replacing clinical expertise emerged as key. Insights into perceived barriers spotlight the need for holistic AI integration infrastructure encompassing training, technical support, ethical oversight, and workflow assistance. Key words: Artificial intelligence, technology zone, machine learning | ||||
| Keywords | ||||
| Key words: Artificial intelligence; technology zone; machine learning | ||||
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