Bibliometric Analysis of Artificial Intelligence and Machine Learning Applications in Healthcare

Abstract

Abstract: This study aims to examine the applications of artificial intelligence (AI) and machine learning (ML) in the healthcare field using bibliometric methods. The main objective of the study is to provide a comprehensive overview of scientific publications based on the keywords “artificial intelligence,” “AI,” “yapay zekâ,” “A.I.,” “machine learning,” “ML,” and “makine öğrenimi.” Bibliometric analysis is a powerful tool for identifying research trends, collaboration networks, and emerging topics by leveraging large data sets. The analysis identified 5,200 studies published between 2020 and 2026. Journal articles published in scientific journals constitute a significant portion of these publications, while research reports and conference abstracts also account for a notable share. The findings were visualized using figures, tables, and maps created with VOSviewer software. The results obtained reveal that AI and ML research in healthcare services is predominantly concentrated in the fields of computer science and medical informatics, while engineering disciplines and basic sciences also make significant contributions to the process. In this context, it has been revealed that the research area examined has gained considerable momentum in recent years. The study provides a comprehensive framework regarding the development trajectory of AI and ML research in healthcare, a multidisciplinary field.