Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study

TLDR

The growing use of AI in health and medicine has spurred extensive research interest over recent decades. This study aims to map the global and historical landscape of AI research in health and medicine. By analyzing 27,451 Web of Science papers from 1977‑2018—84.6 % published 2008‑2018—the authors examined publication trends, author and country collaborations, and keyword networks. The analysis identified key AI techniques (robotics, machine learning, neural networks, NLP) applied mainly to clinical prediction and treatment, with cancer research dominating, followed by heart disease, stroke, vision impairment, Alzheimer’s, and depression, and highlighted gaps in AI studies for other high‑burden diseases, underscoring the need for global protocols and regulations.

Abstract

The increasing application of Artificial Intelligence (AI) in health and medicine has attracted a great deal of research interest in recent decades. This study aims to provide a global and historical picture of research concerning AI in health and medicine. A total of 27,451 papers that were published between 1977 and 2018 (84.6% were dated 2008⁻2018) were retrieved from the Web of Science platform. The descriptive analysis examined the publication volume, and authors and countries collaboration. A global network of authors' keywords and content analysis of related scientific literature highlighted major techniques, including Robotic, Machine learning, Artificial neural network, Artificial intelligence, Natural language process, and their most frequent applications in Clinical Prediction and Treatment. The number of cancer-related publications was the highest, followed by Heart Diseases and Stroke, Vision impairment, Alzheimer's, and Depression. Moreover, the shortage in the research of AI application to some high burden diseases suggests future directions in AI research. This study offers a first and comprehensive picture of the global efforts directed towards this increasingly important and prolific field of research and suggests the development of global and national protocols and regulations on the justification and adaptation of medical AI products.