Integrating artificial intelligence in healthcare practice: challenges and future prospects

Abstract

Aim: To highlight the features of artificial intelligence application in healthcare, with an emphasis on specific AI solutions and the assessment of risks associated with such integration in ethical and regulatory dimensions. Materials and Methods: To achieve the research objective, general scientific theoretical and empirical methods were used, including: bibliosemantic method – analysis of scientific, methodological, psychological, pedagogical literature, and regulatory documents on the research problem, system analysis method – to compare and generalize the experience of using artificial intelligence in healthcare, empirical methods – conversations and interviews with participants in the educational process, modeling – to implement a scheme for providing medical care using AI. Conclusions: Generative artificial intelligence is rapidly developing and is already being used in healthcare. The resources discussed that utilizing artificial intelligence can be used by practicing doctors, patients, as well as higher education students and academic staff in the educational process for examining various clinical cases, better understanding the material, and accessing visualization databases. Therefore, the need to integrate AI technologies into the training process of healthcare professionals at higher medical educational institutions is evident. An important part of the research is addressing the key challengesthat arise when applying AI in medicine: ethical and regulatory issues, as well as the difficulties in integrating with existing medical information systems. Further research should be aimed at developing clear recommendations for medical institutions and educational establishments regarding the implementation and use of AI technologies.