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Performance Deterioration of Deep Learning Models after Clinical
  Deployment: A Case Study with Auto-segmentation for Definitive Prostate
  Cancer Radiotherapy
v1v2 (latest)

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
ArXiv (abs)PDFHTML

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

11 / 11 papers shown
Title
Segmentation by Test-Time Optimization (TTO) for CBCT-based Adaptive
  Radiation Therapy
Segmentation by Test-Time Optimization (TTO) for CBCT-based Adaptive Radiation Therapy
Xiao Liang
J. Chun
H. Morgan
T. Bai
D. Nguyen
Justin C. Park
Steve B. Jiang
34
9
0
08 Feb 2022
A Proof-of-Concept Study of Artificial Intelligence Assisted Contour
  Revision
A Proof-of-Concept Study of Artificial Intelligence Assisted Contour Revision
T. Bai
Anjali Balagopal
M. Dohopolski
H. Morgan
R. Mcbeth
Jun Tan
Mu-Han Lin
David Sher
D. Nguyen
Steve B. Jiang
48
1
0
28 Jul 2021
Deep learning-based COVID-19 pneumonia classification using chest CT
  images: model generalizability
Deep learning-based COVID-19 pneumonia classification using chest CT images: model generalizability
D. Nguyen
F. Kay
Jun Tan
Yulong Yan
Y. Ng
P. Iyengar
R. Peshock
Steve B. Jiang
OOD
65
26
0
18 Feb 2021
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning
Yiding Jiang
Pierre Foret
Scott Yak
Daniel M. Roy
H. Mobahi
Gintare Karolina Dziugaite
Samy Bengio
Suriya Gunasekar
Isabelle M Guyon
Behnam Neyshabur Google Research
OOD
64
55
0
14 Dec 2020
Generalizability issues with deep learning models in medicine and their
  potential solutions: illustrated with Cone-Beam Computed Tomography (CBCT) to
  Computed Tomography (CT) image conversion
Generalizability issues with deep learning models in medicine and their potential solutions: illustrated with Cone-Beam Computed Tomography (CBCT) to Computed Tomography (CT) image conversion
X. Liang
D. Nguyen
Steve B. Jiang
OOD
34
34
0
16 Apr 2020
CheXpedition: Investigating Generalization Challenges for Translation of
  Chest X-Ray Algorithms to the Clinical Setting
CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting
Pranav Rajpurkar
Anirudh Joshi
Anuj Pareek
Phil Chen
Amirhossein Kiani
Jeremy Irvin
A. Ng
M. Lungren
LM&MA
46
49
0
26 Feb 2020
Feature Robustness in Non-stationary Health Records: Caveats to
  Deployable Model Performance in Common Clinical Machine Learning Tasks
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks
Bret A. Nestor
Matthew B. A. McDermott
Willie Boag
G. Berner
Tristan Naumann
Michael C. Hughes
Anna Goldenberg
Marzyeh Ghassemi
OOD
75
112
0
02 Aug 2019
Improving the generalizability of convolutional neural network-based
  segmentation on CMR images
Improving the generalizability of convolutional neural network-based segmentation on CMR images
Chen Chen
Wenjia Bai
R. Davies
A. Bhuva
C. Manisty
...
S. Petersen
E. Lukaschuk
Stefan K. Piechnik
S. Neubauer
Daniel Rueckert
71
120
0
02 Jul 2019
Generalization in Deep Learning
Generalization in Deep Learning
Kenji Kawaguchi
L. Kaelbling
Yoshua Bengio
ODL
109
460
0
16 Oct 2017
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
UQCVBDL
856
9,353
0
06 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg3DV
1.9K
77,441
0
18 May 2015
1