Using Generative AI to create clinical scenarios to improve diagnostic capabilities in specialized consultation for medical students

Background: Given the growing importance of artificial intelligence (AI) in various fields and the necessity of its integration into education, this study was designed with the aim of using Generative AI to create clinical scenarios to improve diagnostic competency in clinical counseling for medical students. Method: This study was a quasi-experimental design. Forty students from Tehran University of Medical Sciences and Iran university of Medical Sciences were conveniently selected and randomly assigned to either an experimental or a control group. The experimental group used AI-based counseling scenarios for ۲۴ days, while the control group received traditional training. The students' diagnostic abilities were measured in terms of accuracy, speed, and differentiation before and after the intervention using a validated and reliable smart tool. All analyses were performed with SPSS ۲۴ software. Results: Based on the study's findings, using Generative AI to create clinical scenarios significantly improved the diagnostic competency of medical students. This novel educational approach was more effective than the traditional method across all dimensions examined, including correct diagnosis (F۱,۳۸=۸.۸۱,P<۰.۰۰۱), diagnostic speed (F۱,۳۸=۵.۴۹,P<۰.۰۰۱), differentiation ability (F۱,۳۸=۶.۲۲,P<۰.۰۰۱), and overall diagnostic competency (F۱,۳۸=۱۳.۴۴,P<۰.۰۰۱). Conclusion: The use of Generative AI is an effective strategy for improving diagnostic competency in clinical counseling for medical students. Key Words: Artificial Intelligence, Clinical Competence, Diagnosis, Reaction Time, Education, Medical

کلیدواژه ها:

Artificial intelligence ، Clinical competence ، Diagnosis ، Reaction time ، Education ، Medical