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.
Highlights
While the growing importance and relevance of artificial intelligence (AI) is indisputable, the term itself has no universally agreed upon definition [1,2]
Based on the Global burden of disease 2017 study, we identified 25 diseases with the highest Disability-Adjusted Life Years (DALYs) and used STATA to extract the number of papers related to Artificial Intelligence (AI) types
We found that AI-related medical research was mainly performed by one to three countries (85.9%)
Summary
While the growing importance and relevance of artificial intelligence (AI) is indisputable, the term itself has no universally agreed upon definition [1,2]. The Cambridge dictionary puts AI as an interdisciplinary approach that adopts principles and devices from a variety of fields, such as computation, mathematics, logics, and biology, to solve the problem of understanding, modeling, and replicating intelligence and cognitive processes [3]. The interest and advances in medical AI applications have surged in recent years, thanks to the substantially enhanced computing power of modern computers [4,9] and the vast amount of digital data available for collection and utilization [1]
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