Machine learning prediction of extended length of stay following endoscopic decompression for lumbar spinal stenosis: A retrospective cohort study
Objective The aims of this study were to develop and validate interpretable ML models for extended length of stay (eLOS) prediction following endoscopic lumbar spinal stenosis (LSS) decompression, and identify modifiable risk factors influencing healthcare costs and recovery. Methods A prospective-r...
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| Main Authors: | Fuqiang Tan, Xiaobin Li, Chaoyang Qu, Xin Shu, Xu Peng |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-07-01
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| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076251361658 |
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