Global trends of machine learning applications in psychiatric research over 30 years: A bibliometric analysis

Abstract

This bibliometric analysis aimed to identify active research areas and trends in machine learning applications within the psychiatric literature. An exponential growth in the number of related publications indexed in Web of Science during the last decade was noted. Document co-citation analysis revealed 10 clusters of knowledge, which included several mental health conditions, albeit with visible structural overlap. Several influential publications in the co-citation network were identified. Keyword trends illustrated a recent shift of focus from "psychotic" to "neurotic" conditions. Despite a relative lack of literature from the developing world, a recent rise in publications from Asian countries was observed. DATA AVAILABILITY: Bibliographic data for this study were downloaded from the Web of Science. The search strategy is included in the Supplementary file.