A deep-learning model using automated performance metrics and clinical features to predict urinary continence recovery after robot-assisted radical prostatectomy-Reference-Cited by-同舟云学术

A deep-learning model using automated performance metrics and clinical features to predict urinary continence recovery after robot-assisted radical prostatectomy

Published:2019-03-20 Issue:3 Volume:124 Page:487-495
ISSN:1464-4096
Container-title:BJU International
language:en
Short-container-title:BJU Int

Author:

Hung Andrew J.¹^ORCID,Chen Jian¹^ORCID,Ghodoussipour Saum¹,Oh Paul J.¹,Liu Zequn²,Nguyen Jessica¹,Purushotham Sanjay³,Gill Inderbir S.¹,Liu Yan⁴

Affiliation:

1. Center for Robotic Simulation and Education; USC Institute of Urology; Keck School of Medicine; University of Southern California; Los Angeles CA USA

2. School of Electronics Engineering and Computer Science; Peking University; Beijing China

3. Department of Information Systems; University of Maryland; Baltimore MD USA

4. Computer Science Department; Viterbi School of Engineering; University of Southern California; Los Angeles CA USA

Funder

Intuitive Surgical Clinical Research

National Institute of Biomedical Imaging and Bioengineering

Publisher

Wiley

Subject

Urology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/bju.14735/fullpdf