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Performance Deterioration of Deep Learning Models after Clinical
  Deployment: A Case Study with Auto-segmentation for Definitive Prostate
  Cancer Radiotherapy

Performance Deterioration of Deep Learning Models after Clinical Deployment: A Case Study with Auto-segmentation for Definitive Prostate Cancer Radiotherapy

11 October 2022
Biling Wang
M. Dohopolski
T. Bai
Junjie Wu
R. Hannan
N. Desai
A. Garant
Daniel Yang
D. Nguyen
Mu-Han Lin
Robert Timmerman
Xinlei Wang
Steve B. Jiang
ArXivPDFHTML

Papers citing "Performance Deterioration of Deep Learning Models after Clinical Deployment: A Case Study with Auto-segmentation for Definitive Prostate Cancer Radiotherapy"

1 / 1 papers shown
Title
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
1