Artificial intelligence in medicine: Clinical applications, ethical implications and challenges in medical training
Year: 2025
Type: article
Abstract: Artificial intelligence (AI) has burst onto the medical scene as a transformative tool, with applications ranging from clinical image analysis to robotic surgery and computational drug discovery. This narrative review aims to critically analyze the role of AI in contemporary medicine, with an emphasis on its clinical, ethical, and educational implications. Technologies such as deep learning, radiomics, autonomous surgical intelligence, and generative models are addressed, as well as their impact on clinical decision-making and the training of future healthcare professionals. Through a critical synthesis of recent literature, the benefits of AI in reducing diagnostic errors, therapeutic personalization, and operational efficiency are examined, along with the risks associated with limited explainability, data security, and professional responsibility. It concludes that AI should not be understood as a substitute for clinical judgment, but rather as a complement that requires new ethical, technical, and cognitive skills in the practice and teaching of medicine.
Authors: De la Cruz, Estrella Rubí Frausto, López, Marco Antonio Jiménez
Institution: Autonomous University of Durango
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W7105807401
FWCI:
Cites:
Cited by:
Related to: