Emerging Technologies in Education: A Bibliometric Analysis of Artificial Intelligence and its Applications in Health Sciences

Abstract

Artificial Intelligence brings a new paradigm in health sciences related to using technologies capable of processing a large amount of patient information to strengthen prediction, prevention and clinical care. This research aimed to perform a bibliometric analysis of Artificial Intelligence and its applications in Health Sciences, particularly on Emerging Technologies in Education. To this end, a search for articles related to "Artificial Intelligence and its Applications in Health Sciences" was conducted at the international level in the Scopus database with search parameters based on titles, abstracts and keywords. The results revealed that the network of the 100 most essential terms was grouped into four clusters, namely: the first cluster identified with red colour is related to artificial Intelligence; the second cluster identified with green colour is related to the controlled study; the third cluster identified with yellow colour is related to algorithm and, the fourth cluster identified with yellow colour is related to education. It was concluded that artificial Intelligence has experienced advances that are having an impact on health sciences education. Academics and researchers have tools that allow them to obtain information to deepen the diagnosis of diseases and present students with robust case studies that strengthen the teaching-learning process.