(untitled) (Research, Society and Development, 2024)
Introduction: In contemporary medicine, Artificial Intelligence (AI) emerges as a revolutionary tool aiding in tasks ranging from the interpretation of medical images, such as computed tomography scans, to the analysis of genomic data. The objective of this research is to investigate how the implementation of Artificial Intelligence (AI) technologies can impact the accuracy and time reduction of imaging diagnoses, in addition to evaluating the effectiveness of treatments. Methodology: This work follows the study methodology proposed by Gil (2002). It consists of an integrative bibliographic review with articles from 2019 to 2024, using the following databases: PubMed, Google Scholar, and SciELO. Results and Discussion: The observed results indicate that the use of deep learning techniques and artificial intelligence (AI) shows great potential in various areas of medicine, particularly in the analysis of medical images and in supporting clinical decision-making. As the implementation of AI in medicine progresses, there is a need for careful consideration of issues such as patient privacy and the need for appropriate regulation to control this activity. Final considerations: It is observed that the use of AI is already a revolutionary reality that is reaching medical practice in image diagnosis. Nonetheless, there are obstacles that need to be overcome for it to be safe, agile, and precise in assisting the physician’s decision regarding the best treatment. Thus, AI should not be considered a threat to the profession but rather a tool that complements the work of doctors, rather than replacing them.