Clinical Applications of Artificial Intelligence in Occupational Health

ObjectivesThe aims of the study are to identify and to critically analyze studies using artificial intelligence (AI) in occupational health.MethodsA 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.ResultsThe 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.ConclusionsWhile AI has potential clinical utility in occupational health, explainable models that are rigorously validated in real-world settings are warranted.