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Published on: December 29, 2023
Clinical Applications of Artificial Intelligence in Occupational Health: A Systematic Literature Review
Zaira S Chaudhry1, Avishek Choudhury
1From the Industrial and Management Systems Engineering, Benjamin M. Statler College of Engineering and Mineral Resources, West Virginia University, Morgantown, West Virginia (Z.S.C, A.C.).
Objectives:
The aims of the study are to identify and to critically analyze studies using artificial intelligence (AI) in occupational health.
Methods:
A systematic search of PubMed, IEEE Xplore, and Web of Science was conducted to identify relevant articles published in English between January 2014-January 2024. Quality was assessed with the validated APPRAISE-AI tool.
Results:
The 27 included articles were categorized as follows: health risk assessment ( n = 17), return to work and disability duration ( n = 5), injury severity ( n = 3), and injury management ( n = 2). Forty-seven AI algorithms were utilized, with artificial neural networks, support vector machines, and random forest being most common. Model accuracy ranged from 0.60-0.99 and area under the curve (AUC) from 0.7-1.0. Most studies ( n = 15) were of moderate quality.
Conclusions:
While AI has potential clinical utility in occupational health, explainable models that are rigorously validated in real-world settings are warranted.
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