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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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Bibliographische Detailangaben
Veröffentlicht in:Head Neck
Hauptverfasser: Goshtasbi, Khodayar, Yasaka, Tyler M., Zandi-Toghani, Mehdi, Djalilian, Hamid R., Armstrong, William B., Tjoa, Tjoson, Haidar, Yarah M., Abouzari, Mehdi
Format: Artigo
Sprache:Inglês
Veröffentlicht: 2020
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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