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Applying interpretable machine learning algorithms to predict risk factors for permanent stoma in patients after TME
OBJECTIVE: The purpose of this study was to develop a machine learning model to identify preoperative and intraoperative high-risk factors and to predict the occurrence of permanent stoma in patients after total mesorectal excision (TME). METHODS: A total of 1,163 patients with rectal cancer were in...
Autores principales: | Liu, Yuan, Zhao, Songyun, Du, Wenyi, Tian, Zhiqiang, Chi, Hao, Chao, Cheng, Shen, Wei |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079943/ https://www.ncbi.nlm.nih.gov/pubmed/37035560 http://dx.doi.org/10.3389/fsurg.2023.1125875 |
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