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Machine Learning to Predict Return to Work After Medical Rehabilitation for Musculoskeletal Disorders: A Retrospective Cohort Study

Mathis Elling et al.

Journal of Occupational Rehabilitation2026https://doi.org/10.1007/s10926-025-10359-3article
AJG 2
Weight
0.50

What the paper says

The machine learning model demonstrated good predictive performance for RTW after medical rehabilitation for musculoskeletal disorders and confirmed the relevance of established predictors, such as prior employment and incapacity for work. In addition, the analysis identified interactions that are difficult to detect with traditional regression approaches.

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Cite this paper

https://doi.org/https://doi.org/10.1007/s10926-025-10359-3

Or copy a formatted citation

@article{mathis2026,
  title        = {{Machine Learning to Predict Return to Work After Medical Rehabilitation for Musculoskeletal Disorders: A Retrospective Cohort Study}},
  author       = {Mathis Elling et al.},
  journal      = {Journal of Occupational Rehabilitation},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s10926-025-10359-3},
}

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Machine Learning to Predict Return to Work After Medical Rehabilitation for Musculoskeletal Disorders: A Retrospective Cohort Study

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.