Inteligencia artificial aplicada a la capacidad predictiva y diagnóstica de enfermedades crónicas

Abstract

Introduction: Artificial intelligence (AI) is the foundation on which human intelligence processes are replicated, based on the creation and use of algorithms with big data. AI has become an essential aspect in medicine, this being one of the most influential fields for the protection of human health, in order to improve care by streamlining processes and diagnostic precision for improving health. Objective: Explore how artificial intelligence is capable of improving the predictive and diagnostic capacity of chronic diseases, through the review of updated scientific literature. Methods: A search and selection of high-impact scientific articles from the last 5 years was carried out through search engines such as Pubmed, UpToDate, and Google Scholar. Development: Medicine has experienced technological advances that have allowed medical discoveries, both in terms of diagnosis and treatment, this has led to a significant improvement in the quality of life of patients and has greatly increased the opportunities for recovery. Through AI systems, it is possible to anticipate pathological entities in an individual and consider solutions that could be used to address health issues, in this way being able to foresee future situations, avoiding possible complications and starting treatment in the early stages of the disease. Conclusions: In this review we have been able to show that the implications that AI has in favor of health in terms of prediction and diagnosis of diseases are innumerable.