Artificial intelligence in the training system of future doctors
 
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I.HORBACHEVSKY TERNOPIL NATIONAL MEDICAL UNIVERSITY, TERNOPIL, UKRAINE
 
 
Publication date: 2025-11-30
 
 
Wiadomości Lekarskie 2025;(11):2481-2488
 
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ABSTRACT Aim: To analyze the potential of artificial intelligence in the process of solving innovative ideas in the system of training future doctors, improving the educational process in medical universities, and analyzing the concept of quot; health and quot; as a key term in professional activity. In order to achieve the stated goal, we plan to examine the importance of this concept for regulatory documents and propose an original (authorial) solution to these issues. Materials and Methods: A systematic literature search was carried out in the following databases: PubMed, Scopus, Web of Science, Google Scholar. Additional grey literature was identified through institutional repositories, conference proceedings, and relevant policy documents of the Ukrainian government and the European Union. Such keywords and their combinations as “artificial intelligence”, “medical education”, “empathy”, “anamnesis”, “academic integrity”, “iatrogenesis”, “digital transformation”, “higher medical school”, “information culture”, “AI in healthcare”, “Poland”, “Ukraine” were used. Inclusion criteria encompassed peer-reviewed articles published between 2018 and 2025 in English, Ukrainian, or Polish that focused on the use of AI in medical education, clinical training, and healthcare organization, as well as studies analyzing its advantages, limitations, ethical considerations, and offering comparative or practical recommendations. Exclusion criteria included non-scientific sources, articles unrelated to medical education or healthcare, and studies lacking clear methodology or outcome measures. Conclusions: Artificial intelligence in organizing the administrative work of medical institutions has the significant potential. This refers to information about staff and patients, organizing communication schedules with specialists of the relevant profile, and optimizing schedules.
eISSN:2719-342X
ISSN:0043-5147
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