Examinando por Autor "Ramirez Mayon, Maria Emilia"
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Ítem Embargo Inteligencia artificial en la formación médica(Universidad Católica de Cuenca., 2024) Ramirez Mayon, Maria Emilia; Bravo Pesántez, Claudio Esteban; 0107478216Background: The integration of artificial intelligence (AI) in medical education, both at the undergraduate and graduate levels, has been gaining prominence in recent years, becoming essential in several areas due to its great potential to optimize and reduce research time, establish new lines of study, improve prevention and early detection of diseases, increase the quality of medical care and, therefore, the quality of life of patients. Methodology: A literature review was conducted. It included descriptive, analytical, and experimental scientific articles from journals indexed in Spanish and English from quartiles 1 to 4 in databases such as PubMed, ScienceDirect, Scopus, SciELO, Springer, and IEEE. English and Spanish keywords were applied, and Boolean operators were used. The information was collected following the PRISMA Guide. Data was recorded in customized tables, and the outcomes were consolidated in customized tables aligned with the objectives. Results: After the search, 351 articles were identified; however, after applying the eligibility criteria, only 16 were selected. Most of the studies consulted support the multiple benefits of incorporating AI in the training of doctors at both undergraduate and postgraduate levels, in addition to the wide variety of available technologies that contribute not only theoretically but practically to providing students with real-life scenarios to apply their knowledge into practice. This enhances their teaching-learning process. Conclusions: With the integration of AI in medical training, significant benefits can be obtained by enhancing students' skills both at a theoretical and practical level. However, teachers must provide supervision in case of potential doubts or concerns, in addition to the constant updating from both parties based on reliable information of high scientific relevance.
