Medical Specialties Involved in Artificial Intelligence Research: Is There a Leader

Abstract

Objective Research in artificial intelligence area appears to have been taken up by different specialties with varying enthusiasm. We compared the contribution of different medical specialties to machine learning, deep learning, and artificial intelligence research over 30 years. Methods The Web of Science database was searched retrospectively for the terms “artificial intelligence”, “machine learning” and “deep learning”. Results were limited to articles, proceedings papers, or reviews published in Web of Science categories mapped to the OECD 3.02 Clinical Medicine schema between the year 1988 and 2018. A list of international medical specialties was assembled, a search tool was created to query author affiliation data, and analysis performed to assess specialty publication over time and inter-specialty collaboration. Publication differences between specialties were evaluated for significance with two-tail unpaired t-test. Results Initial database search returned 3937 unique results once duplicates were removed. Medical specialty analysis returned 2381 papers from 789 different journals. Radiology published significantly more papers than other top specialties (p < 0.001), being involved in 783 papers (33% of returned total), followed by psychiatry (406 papers) and neurology (287 papers). Conclusion There has been an exponentially increase in yearly publications involving artificial intelligence, machine learning, and deep learning over the last 30 years. Radiology is the leading medical speciality in machine learning, deep learning, and artificial intelligence research in terms of volume of yearly publications and overall citations, followed by psychiatry and neurology.

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