Evaluation of Uşak University Medical Faculty students' preparedness for artificial intelligence and its application in healthcare

Aim: Artificial Intelligence (AI) is a subfield of computer science that enables computer systems to model human cognitive abilities, allowing them to perform functions such as thinking, data analysis, learning, problem-solving, and decision-making. AI has made an impact in the healthcare sector, as in many other fields. For AI to be effectively implemented in healthcare, it is crucial for medical professionals to be among those guiding the technology. Although AI has not yet been fully integrated, future medical school graduates are expected to utilize this technology in clinical practice. In this study, our aim is to assess the preparedness levels of future physicians regarding AI and its applications in healthcare, identify related factors, and raise awareness on the subject. Materials and Methods: This study was conducted between 01.10.2024 and 01.12.2024 to evaluate the preparedness levels of Uşak University Faculty of Medicine students regarding AI and its applications in healthcare. Participants were included in the study on a voluntary basis, and after providing the necessary explanations about the study, their written consent was obtained. The survey consists of two sections. The first section includes 17 questions that examine the sociodemographic characteristics of the students and the factors that may affect their AI readiness levels. In the second section, the Medical Artificial Intelligence Readiness Scale, consisting of a total of 22 questions, was used (1). Data analysis was performed using appropriate statistical tests in the IBM SPSS.27 program. Results: A total of 256 medical students participated in the study (54.3% female, 45.7% male; mean age 21.71±2.31). Among the participants, 66.8% believed that AI should be used in the field of healthcare, and 77.3% thought that medical AI applications could be integrated into medical practice in the future to provide supportive functions. Additionally, 77.7% of the participants stated that the medical school curriculum should include information about AI and its use in healthcare. Female participants had significantly higher scores in cognitive, foresight, ethics, and total scale scores (p<0.05). No significant difference was found in the skills factor. Students who had taken a course on Artificial Intelligence or Robotic Medicine had significantly higher total scale scores compared to those who had not (p<0.001). The mean total score of the Medical Artificial Intelligence Readiness Scale was found to be 45.66±18.84. A positive correlation was detected among the sub-dimension scores of the Medical Artificial Intelligence Readiness Scale (p<0.001). Conclusions: When evaluating the readiness levels of Uşak University Faculty of Medicine students regarding AI and its use in healthcare, the results revealed that the majority of students believed AI could make significant contributions to the healthcare field. However, they experienced shortcomings in access to AI-related information, education, and practical applications. Most students stated that the medical school curriculum should include information about AI and its applications in healthcare. It was found that students who received AI-related education had a higher level of readiness. Our study emphasized the need to enhance AI integration in medical education.