(untitled) (CIPEEX, 2025)
Artificial intelligence (AI) has established itself as a powerful tool in healthcare, especially in computer-assisted medical diagnosis. This study aimed to analyze the contributions of AI in the interpretation of medical images and its potential to improve diagnostic accuracy. The methodology consisted of a literature review of articles indexed in the PubMed and Scopus databases, focusing on the use of machine learning algorithms in radiology, cardiology, and neurology. The results demonstrated that convolutional neural networks are capable of detecting early signs of diseases such as cancer, Alzheimer’s, and cardiovascular conditions, often surpassing human accuracy in specific tasks. In addition, AI reduces diagnostic errors and optimizes hospital management through the integration of electronic medical records. However, challenges remain, such as the need for diverse databases, algorithm transparency, and patient data protection. It is concluded that AI represents an innovative advance for diagnostic medicine, but its safe and effective implementation requires professional training and strict regulations.