Using Ensemble Machine Learning: A Multifaceted Approach to Predicting Rehabilitation Outcomes

Rocco de Filippis, Abdullah Al Foysal

Open source

DOI: 10.9734/bpi/dhrni/v8/2486
Published: 2024-10-03
Container: Disease and Health Research: New Insights Vol. 8
Publisher: BP International
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.9734/bpi/dhrni/v8/2486,
  title = {Using Ensemble Machine Learning: A Multifaceted Approach to Predicting Rehabilitation Outcomes},
  author = {Rocco de Filippis and Abdullah Al Foysal},
  year = {2024},
  journal = {Disease and Health Research: New Insights Vol. 8},
  doi = {10.9734/bpi/dhrni/v8/2486},
  url = {https://doi.org/10.9734/bpi/dhrni/v8/2486}
}

RIS

TY  - JOUR
TI  - Using Ensemble Machine Learning: A Multifaceted Approach to Predicting Rehabilitation Outcomes
AU  - Rocco de Filippis
AU  - Abdullah Al Foysal
PY  - 2024
JO  - Disease and Health Research: New Insights Vol. 8
DO  - 10.9734/bpi/dhrni/v8/2486
UR  - https://doi.org/10.9734/bpi/dhrni/v8/2486
ER  -

APA

Filippis, R. D., & Foysal, A. A. (2024). Using Ensemble Machine Learning: A Multifaceted Approach to Predicting Rehabilitation Outcomes. Disease and Health Research: New Insights Vol. 8. https://doi.org/10.9734/bpi/dhrni/v8/2486

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crossref · retrieved 2026-09-25T21:56:39.063Z