Artificial Intelligence methods in the diagnosis and treatment of chronic diseases (#1574)

Authors

Medina-Perez, Gerald P.

Castillo-Pastrana, Nicole B.

Vasquez-Garcia, Claudio M.

Alegria-La Rosa-de Benavides, Lourdes M.

Abstract

The use of artificial intelligence is being progressively introduced in the diagnosis and treatment of patients or people with chronic diseases. The objective of this SLR is to identify which AI methods are of help in the health sector for the diagnosis and treatment of chronic diseases, thus saving many lives and managing to help the patient in the whole process of their treatment. As a search method, 14255 articles were obtained in Scopus and searched from 2019 to 2023, obtaining 20 articles after applying the exclusion and inclusion criteria. The expansion of artificial intelligence methods positioned machine learning at 30% and various artificial intelligence methods at 15%, with diagnosis being the most important medical study approach in chronic diseases. It was concluded that machine learning is the most relevant concerning precision between 65% and 91.4% and accuracy of 89%, with diagnosis having 55% of the total articles in which machine learning is mentioned covering physiological or physical diseases, pulmonary, and diabetes.