Identifying Clinical Sub-Groups Using Machine Learning: Functional Status, Symptom Burden, and Healthcare Utilisation From National Palliative Care Data.
- DOI
- 10.1177/10499091261491646
- Published
- 2026 Sep 23
- Container
- The American journal of hospice & palliative care
- Publisher
- Not recorded
- Open access
- unknown
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1177/10499091261491646,
title = {Identifying Clinical Sub-Groups Using Machine Learning: Functional Status, Symptom Burden, and Healthcare Utilisation From National Palliative Care Data.},
author = {Migiddorj B and Currow D and Batterham M and Win KT},
year = {2026},
journal = {The American journal of hospice \& palliative care},
doi = {10.1177/10499091261491646},
url = {https://doi.org/10.1177/10499091261491646}
}RIS
TY - JOUR TI - Identifying Clinical Sub-Groups Using Machine Learning: Functional Status, Symptom Burden, and Healthcare Utilisation From National Palliative Care Data. AU - Migiddorj B AU - Currow D AU - Batterham M AU - Win KT PY - 2026 JO - The American journal of hospice & palliative care DO - 10.1177/10499091261491646 UR - https://doi.org/10.1177/10499091261491646 ER -
APA
B, M., D, C., M, B., & KT, W. (2026). Identifying Clinical Sub-Groups Using Machine Learning: Functional Status, Symptom Burden, and Healthcare Utilisation From National Palliative Care Data.. The American journal of hospice & palliative care. https://doi.org/10.1177/10499091261491646
Source records
- pubmed · retrieved 2026-09-25T20:44:54.588Z