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Uncertainty-Informed Deep Learning Models Enable High-Confidence
  Predictions for Digital Histopathology

Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital Histopathology

9 April 2022
J. Dolezal
Andrew Srisuwananukorn
D. Karpeyev
S. Ramesh
S. Kochanny
B. Cody
A. Mansfield
S. Rakshit
R. Bansal
M. Bois
A. Bungum
Jefree J. Schulte
E. Vokes
M. Garassino
A. Husain
A. Pearson
    OOD
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Papers citing "Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital Histopathology"

8 / 8 papers shown
Title
Implementing Trust in Non-Small Cell Lung Cancer Diagnosis with a Conformalized Uncertainty-Aware AI Framework in Whole-Slide Images
Xiaoge Zhang
Tao Wang
Chao Yan
Fedaa Najdawi
Kai Zhou
Yuan Ma
Yiu-ming Cheung
Bradley Malin
MedIm
42
0
0
03 Jan 2025
Conditional Shift-Robust Conformal Prediction for Graph Neural Network
Conditional Shift-Robust Conformal Prediction for Graph Neural Network
Akansha Agrawal
UQCV
53
1
0
20 May 2024
General Place Recognition Survey: Towards Real-World Autonomy
General Place Recognition Survey: Towards Real-World Autonomy
Peng Yin
Jianhao Jiao
Shiqi Zhao
Lingyun Xu
Guoquan Huang
Howie Choset
Sebastian A. Scherer
Jianda Han
47
7
0
08 May 2024
Artificial Intelligence for Digital and Computational Pathology
Artificial Intelligence for Digital and Computational Pathology
Andrew H. Song
Guillaume Jaume
Drew F. K. Williamson
Ming Y. Lu
Anurag J. Vaidya
Tiffany R. Miller
Faisal Mahmood
AI4CE
30
130
0
13 Dec 2023
A review of uncertainty quantification in medical image analysis:
  probabilistic and non-probabilistic methods
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods
Ling Huang
S. Ruan
Yucheng Xing
Mengling Feng
41
20
0
09 Oct 2023
A Review of Uncertainty Estimation and its Application in Medical
  Imaging
A Review of Uncertainty Estimation and its Application in Medical Imaging
K. Zou
Zhihao Chen
Xuedong Yuan
Xiaojing Shen
Meng Wang
Huazhu Fu
UQCV
46
86
0
16 Feb 2023
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,661
0
05 Dec 2016
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
285
9,138
0
06 Jun 2015
1