TRENDS IN MEDICAL EDUCATION IN THE AGE OF ADVANCED TECHNOLOGY AND ARTIFICIAL INTELLIGENCE: AN INTEGRATIVE REVIEW
Palavras-chave:
Education, Medical, Generative Artificial Intelligence, Technology, Humanization, InnovationResumo
Medical education is undergoing changes resulting from the digitization of healthcare systems, advances in artificial intelligence, and the need to integrate technological and humanistic aspects into patient care. In this scenario, it is essential to rethink curricula and methodologies in medical education.The objective of this study was to review the main trends in medical education in the context of advanced technology and artificial intelligence.A narrative review of the literature was conducted using the following keywords: medical education, artificial intelligence, technology, innovation, and humanization. Articles published in national and international databases were analyzed. Four trends have stood out in contemporary medical education: (1) a humanistic approach to medical practice, with an emphasis on empathy, ethics, and interprofessional collaboration; (2) early experience and longitudinal integration, promoting early contact with patients and continuous learning; (3) the need to go beyond hospitals toward society, incorporating cultural diversity, social responsibility, and attention to community demands; and (4) student-centered learning with technological support, favoring active methodologies, personalization, collaborative interaction, and greater access to digital resources.It is concluded that medical education should integrate technological innovation and humanistic values, ensuring the training of physicians who are better prepared for complex global contexts and patient-centered care.
Referências
Reference:
HAN, Eui-Ryoung; PARK, Seung-Hoon; LEE, Ji-Hye; KIM, Min-Soo. Trends in Medical
Education in the Era of Advanced Technology and Artificial Intelligence: a Narrative
Review. BMC Medical Education, [S.l.], v. 19, n. 1, p. 460, 2019
Available at: https://pubmed.ncbi.nlm.nih.gov/31829208/