APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN MEDICAL DIAGNOSIS

Resumo

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.