A retrospective study using machine learning to develop predictive model to identify urinary infection stones in vivo

Preoperative diagnosis of urinary infection stones is difficult, and accurate detection of stone composition can only be performed ex vivo. To provide guidance for better perioperative management and postoperative prevention of infection stones, we developed a machine learning model for preoperative...

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Detalles Bibliográficos
Autores principales: Wu, Yukun, Mo, Qishan, Xie, Yun, Zhang, Junlong, Jiang, Shuangjian, Guan, Jianfeng, Qu, Canhui, Wu, Rongpei, Mo, Chengqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232574/
https://www.ncbi.nlm.nih.gov/pubmed/37256418
http://dx.doi.org/10.1007/s00240-023-01457-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232574/
https://www.ncbi.nlm.nih.gov/pubmed/37256418
http://dx.doi.org/10.1007/s00240-023-01457-z

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