Applications of artificial intelligence in medicine

Abstract

Artificial intelligence (AI) in medicine has transformed key areas such as diagnosis, treatment personalization, and the optimization of clinical processes, significantly improving the precision and efficiency of healthcare. This study aimed to analyze the impact of AI in medicine, focusing on its practical applications in medical imaging, robot-assisted surgery, and the prediction of epidemiological outbreaks. An explanatory and documentary bibliographic design was employed, based on the qualitative analysis of 15 articles selected from scientific databases such as PubMed, Oxford Academic, and Cochrane Library, published between 2019 and 2024. The methodology included a systematic review with strict inclusion and exclusion criteria to ensure the clinical relevance and timeliness of the data, prioritizing aspects such as diagnostic techniques, clinical efficacy, and ethical challenges. The results highlight that AI has substantially improved diagnostic accuracy and hospital efficiency, with innovative applications in teledermatology, medical imaging, and personalized oncology treatments, in addition to reducing medical errors and optimizing clinical resources. However, significant barriers to its widespread adoption persist, primarily related to the lack of transparency in algorithms and concerns about the privacy and security of medical data. It is concluded that AI is a powerful tool for modern medicine, but its successful integration depends on the development of robust ethical regulations and the promotion of equity in its applications, ensuring safe, efficient, and reliable implementation in clinical practice.