Use of Artificial Intelligence in Child Health: A Bibliometric Analysis

Abstract

The aim of this study is to examine the existing scientific literature on the use of artificial intelligence (AI) in the field of child health through a bibliometric analysis. In this context, the study aims to identify publication trends in the field and reveal existing research gaps. On September 4, 2025, a search was conducted in the Web of Science (WoS) database using terms such as “artificial intelligence,” “children,” “health,” and “care,” resulting in 495 articles being included in the analysis. The bibliometric evaluation was performed using the Biblioshiny interface. Publication years, keywords, and countries were analyzed. A total of 4,509 authors contributed to the 495 articles published between 1999 and 2025. The country with the highest number of publications was identified as the United States. According to the Keywords Plus analysis, the most frequently used terms were “artificial intelligence” (n=241, 19%), “children” (n=153, 12%), “machine learning” (n=99, 8%), “care” (n=30, 4%), and “diagnosis” (n=37, 3%). This indicates that scientific output on the use of AI in the field of child health has increased in recent years. Publication trends highlight that the topic has attracted significant international attention, yet some research gaps exist in the literature, underscoring the need for more comprehensive studies.