A multicenter study on the application of artificial intelligence radiological characteristics to predict prognosis after percutaneous nephrolithotomy

BACKGROUND: A model to predict preoperative outcomes after percutaneous nephrolithotomy (PCNL) with renal staghorn stones is developed to be an essential preoperative consultation tool. OBJECTIVE: In this study, we constructed a predictive model for one-time stone clearance after PCNL for renal stag...

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Detalles Bibliográficos
Autores principales: Hou, Jian, Wen, Xiangyang, Qu, Genyi, Chen, Wenwen, Xu, Xiang, Wu, Guoqing, Ji, Ruidong, Wei, Genggeng, Liang, Tuo, Huang, Wenyan, Xiong, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Endocrinology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10541026/
https://www.ncbi.nlm.nih.gov/pubmed/37780621
http://dx.doi.org/10.3389/fendo.2023.1184608

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10541026/
https://www.ncbi.nlm.nih.gov/pubmed/37780621
http://dx.doi.org/10.3389/fendo.2023.1184608

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