Forecasting Trajectories of Physiological Mechanics with Sparse Clinical Data Using a Data Assimilation and Machine Learning Hybrid
- DOI
- 10.64898/2026.07.22.26358695
- Published
- 2026-07-24
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- Not recorded
- Publisher
- openRxiv
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.64898/2026.07.22.26358695,
title = {Forecasting Trajectories of Physiological Mechanics with Sparse Clinical Data Using a Data Assimilation and Machine Learning Hybrid},
author = {Yanran Wang and J.N. Stroh and Debashis Ghosh and Melike Sirlanci and George Hripcsak and Tellen D. Bennett and D.J. Albers},
year = {2026},
doi = {10.64898/2026.07.22.26358695},
url = {https://doi.org/10.64898/2026.07.22.26358695}
}RIS
TY - JOUR TI - Forecasting Trajectories of Physiological Mechanics with Sparse Clinical Data Using a Data Assimilation and Machine Learning Hybrid AU - Yanran Wang AU - J.N. Stroh AU - Debashis Ghosh AU - Melike Sirlanci AU - George Hripcsak AU - Tellen D. Bennett AU - D.J. Albers PY - 2026 DO - 10.64898/2026.07.22.26358695 UR - https://doi.org/10.64898/2026.07.22.26358695 ER -
APA
Wang, Y., Stroh, J., Ghosh, D., Sirlanci, M., Hripcsak, G., Bennett, T. D., & Albers, D. (2026). Forecasting Trajectories of Physiological Mechanics with Sparse Clinical Data Using a Data Assimilation and Machine Learning Hybrid. https://doi.org/10.64898/2026.07.22.26358695
Source records
- crossref · retrieved 2026-09-25T15:14:51.353Z