سامانه همایش های دانشگاه آزاد اسلامی واحد نجف آباد

صفحه اصلی / International Conference on Artificial Intelligence; City, Industry and Health

Comparison of the use of two methods of artificial intelligence and Case Base Learning on clinical decision-making of medical students

نویسندگان :

Arezoo Vasili¹ Hamid Reza Nikyar² Ramtin Akbari³

1- 1. Department of Medicine, Na.C., Islamic Azad University, Najafabad, Iran 2- 1. Department of Medicine, Na.C., Islamic Azad University, Najafabad, Iran 3- 1. Department of Medicine, Na.C., Islamic Azad University, Najafabad, Iran

کلمات کلیدی :

Artificial Intelligence،Patient-Centered Clinical Education،Clinical Decision Making،Medical Students

چکیده :

Artificial intelligence, especially approaches based on machine learning, deep learning, natural language processing, and decision support systems, can be used as effective strategies in transforming the process of producing and implementing clinical guidelines and solving the challenges in this field. This study aimed to compare the use of two methods, artificial intelligence and patient-centered clinical education, on clinical decision-making of medical students. This is a case-control study conducted on 70 medical students in their medical internship in the internal medicine department of a teaching hospital in 1403. Finally, the results in the areas of data analysis, evidence synthesis, clinical decision-making and reasoning, patient communication, history taking, treatment planning and management were evaluated using the DOPS checklist, and the two groups were compared using t-tests using SPSS software. The results show that in all areas except the area of patient communication skills, the average scores of the case group that used a combination of patient-centered education and AI were significantly higher than the control group (P≤0.05). Artificial intelligence has the potential to improve the traditional approach to guideline production and implementation. Collaboration between AI experts, healthcare professionals, and policymakers is essential to ensure that the role of AI in clinical guidelines continues to grow and improve as a valuable tool in improving patient outcomes, promoting evidence-based decision-making, and shaping the future of health and care.