Systematic review highlights machine learning's potential to predict burnout in healthcare workers, suggesting improved study design and data integration.
ML models show promise for predicting burnout in HCWs but are limited by methodological weaknesses, heterogeneity, and lack of external validation. Advancing this field requires rigorous design, transparent reporting, multimodal data integration, and ethical safeguards to enable trustworthy clinical use.
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Shi et al. (2025) studied this question.
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