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Automated machine learning to predict the difficulty for endoscopic resection of gastric gastrointestinal stromal tumor
BACKGROUND: Accurate preoperative assessment of surgical difficulty is crucial to the success of the surgery and patient safety. This study aimed to evaluate the difficulty for endoscopic resection (ER) of gastric gastrointestinal stromal tumors (gGISTs) using multiple machine learning (ML) algorith...
Autores principales: | Liu, Luojie, Zhang, Rufa, Shi, Dongtao, Li, Rui, Wang, Qinghua, Feng, Yunfu, Lu, Fenying, Zong, Yang, Xu, Xiaodan |
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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/PMC10206233/ https://www.ncbi.nlm.nih.gov/pubmed/37234977 http://dx.doi.org/10.3389/fonc.2023.1190987 |
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