Como a inteligência artificial pode ajudar no monitoramento pós-cirúrgico

Abstract

The integration of Artificial Intelligence (AI) in healthcare is revolutionizing the medical landscape, bringing innovative advances in diagnosis, treatment and disease management. Technologies such as machine learning and deep learning enable analysis of large volumes of clinical data, medical images and genetic information, identifying complex patterns relevant to personalized medicine and healthcare efficiency. Given this scenario, this study aims to investigate the impact of AI on healthcare, focusing on its practical applications, implementation challenges and benefits for diagnosis, treatment and disease management. To this end, the methodology of an exploratory bibliographic review was used, mapping the current state of knowledge about AI in healthcare, identifying gaps in the literature and understanding emerging trends. In view of the above, it is concluded that AI is evolving medical practice by offering more accurate and faster diagnoses, personalizing treatments and improving operational efficiency. Successful examples include the use of algorithms for medical image analysis, post-surgical monitoring with AI, and the implementation of smart medical devices such as robotic prosthetics and remote monitoring systems. These advances improve patients' quality of life and reduce operating costs. The continued evolution of AI, integrated with data from wearable devices and mobile apps, promises even more innovations, bolstering a more efficient and accessible patient-centric healthcare system.