WoS Driven Bibliometric Analysis on Genetic Disease Prediction Using Artificial Intelligence

The term “artificial intelligence” (AI) is used to describe the practice of simulating human intelligence in a machine. Robotics, medical diagnostics, medical statistics, and even human biology are just a few of the applications of artificial intelligence. This article aims to provide a bibliometric analysis of artificial intelligence's potential applications in predicting genetic diseases from 2018 to 2023. The primary objective of this research is to evaluate the available data on the efficacy of using AI for the prevention of hereditary illnesses. The study's authors acknowledged and affirmed the issue's significance and the topic's potential to aid future academics in achieving strategic alignment between information and technology. There have been a total of 127 articles on this subject, all of which have been analyzed using the Web of Science bibliometric technique. Articles, conference papers, and book chapters all contribute to this bibliometric study, which is used to gauge the worldwide influence of publications in a certain field. This article reviews the best practices for doing and using bibliometric research using the R software package. In the realm of genetic disease prediction, visualization makes it simple to view and comprehend various approaches.