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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Detalhes bibliográficos
Publicado no:Head Neck
Main Authors: Goshtasbi, Khodayar, Yasaka, Tyler M., Zandi-Toghani, Mehdi, Djalilian, Hamid R., Armstrong, William B., Tjoa, Tjoson, Haidar, Yarah M., Abouzari, Mehdi
Formato: Artigo
Idioma:Inglês
Publicado em: 2020
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Article
Acesso em linha: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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