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Machine Learning Models to Predict Length of Stay and Discharge Destination in Complex Head and Neck Surgery
BACKGROUND: This study develops machine learning (ML) algorithms that use preoperative-only features to predict discharge-to-nonhome-facility (DNHF) and length-of-stay (LOS) following complex head and neck surgeries. METHODS: Patients undergoing laryngectomy or composite tissue excision followed by...
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| Veröffentlicht in: | Head Neck |
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| Hauptverfasser: | , , , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2020
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7904593/ https://ncbi.nlm.nih.gov/pubmed/33142001 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/hed.26528 |
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