Deep learning on automated performance metrics and clinical features to predict urinary continence recovery after robot-assisted radical prostatectomy

OBJECTIVES: To predict urinary continence recovery after robot-assisted radical prostatectomy (RARP) utilizing a deep learning (DL) model, which was then used to evaluate surgeon’s historical patient outcomes. SUBJECTS AND METHODS: Robotic surgical automated performance metrics (APMs) during RARPs,...

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Bibliografski detalji
Izdano u:BJU Int
Glavni autori: Hung, Andrew J., Chen, Jian, Ghodoussipour, Saum, Oh, Paul J., Liu, Zequn, Nguyen, Jessica, Purushotham, Sanjay, Gill, Inderbir S., Liu, Yan
Format: Artigo
Jezik:Inglês
Izdano: 2019
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Article
Online pristup:https://ncbi.nlm.nih.gov/pmc/articles/PMC6706286/
https://ncbi.nlm.nih.gov/pubmed/30811828
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/bju.14735
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