Comparative analysis shows that AI improves clinical skills and task efficiency in medical students, highlighting key challenges.
The purpose of this article is to study the effectiveness of integrating artificial intelligence into medical education and to identify the key advantages, challenges, and prospects. A comparative analysis of the implementation of artificial intelligence technologies in Kyrgyzstan, Kazakhstan, Tajikistan, Canada, Germany, Austria, and Switzerland was carried out. Randomised controlled trials, meta-analyses, systematic reviews, and surveys were used to assess the effectiveness of introducing artificial intelligence into medical university curricula. It was found that the use of artificial intelligence technologies helps to reduce task completion time by an average of 35 minutes, improve clinical skills (effect 0.68; 95% CI: 0.30-1.06, p<0.001) and increase satisfaction with the learning process (effect 0.46; 95% CI: 0.26-0.66, p<0.001). The level of knowledge about artificial intelligence was studied, which was 0.4 (95% CI: 0.3-0.5, p<0.01), and the positive attitude of students towards its use was 0.7 (95% CI: 0.6-0.8, p<0.01). It has been shown that adaptive learning systems based on artificial intelligence improve diagnostic skills, accuracy of clinical decisions, and situation modelling. Virtual and augmented reality contribute to the safe development of skills. The challenges of implementing technologies are identified, including the need for ethical standards, minimising algorithmic biases, and preparing teachers.
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kyzy et al. (2025) studied this question.
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