A dynamic stacking machine learning framework and prototype software module for real-time hemodialysis hypotension monitoring
- DOI
- 10.4103/jrms.jrms_216_25
- Published
- 2026-07
- Container
- Journal of Research in Medical Sciences
- Publisher
- Ovid Technologies (Wolters Kluwer Health)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.4103/jrms.jrms_216_25,
title = {A dynamic stacking machine learning framework and prototype software module for real-time hemodialysis hypotension monitoring},
author = {Bin Ji and Jianhua Dong and Minghong Zhang and Yunzhang Cheng and Tianyi Zhang and Mingwei Zhang},
year = {2026},
journal = {Journal of Research in Medical Sciences},
doi = {10.4103/jrms.jrms_216_25},
url = {https://doi.org/10.4103/jrms.jrms_216_25}
}RIS
TY - JOUR TI - A dynamic stacking machine learning framework and prototype software module for real-time hemodialysis hypotension monitoring AU - Bin Ji AU - Jianhua Dong AU - Minghong Zhang AU - Yunzhang Cheng AU - Tianyi Zhang AU - Mingwei Zhang PY - 2026 JO - Journal of Research in Medical Sciences DO - 10.4103/jrms.jrms_216_25 UR - https://doi.org/10.4103/jrms.jrms_216_25 ER -
APA
Ji, B., Dong, J., Zhang, M., Cheng, Y., Zhang, T., & Zhang, M. (2026). A dynamic stacking machine learning framework and prototype software module for real-time hemodialysis hypotension monitoring. Journal of Research in Medical Sciences. https://doi.org/10.4103/jrms.jrms_216_25
Source records
- crossref · retrieved 2026-11-07T10:08:29.282Z