A semi-supervised clustering approach for prediction and inference with multidimensional longitudinal outcomes
- DOI
- 10.1007/s10742-025-00366-5
- Published
- 2025-12-06
- Container
- Health Services and Outcomes Research Methodology
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s10742-025-00366-5,
title = {A semi-supervised clustering approach for prediction and inference with multidimensional longitudinal outcomes},
author = {Booil Jo and Trevor J. Hastie and Zetan Li and Qianheng Ma and Lara C. Foland-Ross and Nelly Mauras and Allan L. Reiss},
year = {2025},
journal = {Health Services and Outcomes Research Methodology},
doi = {10.1007/s10742-025-00366-5},
url = {https://doi.org/10.1007/s10742-025-00366-5}
}RIS
TY - JOUR TI - A semi-supervised clustering approach for prediction and inference with multidimensional longitudinal outcomes AU - Booil Jo AU - Trevor J. Hastie AU - Zetan Li AU - Qianheng Ma AU - Lara C. Foland-Ross AU - Nelly Mauras AU - Allan L. Reiss PY - 2025 JO - Health Services and Outcomes Research Methodology DO - 10.1007/s10742-025-00366-5 UR - https://doi.org/10.1007/s10742-025-00366-5 ER -
APA
Jo, B., Hastie, T. J., Li, Z., Ma, Q., Foland-Ross, L. C., Mauras, N., & Reiss, A. L. (2025). A semi-supervised clustering approach for prediction and inference with multidimensional longitudinal outcomes. Health Services and Outcomes Research Methodology. https://doi.org/10.1007/s10742-025-00366-5
Source records
- crossref · retrieved 2026-11-10T11:38:33.905Z