Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis | Paper Citation Record

Observation 9b021a14-1c96-49b2-8417-d40e2ae34335 · outbound

This paper cites On calibration of modern neural networks.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis On calibration of modern neural networks

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This paper cites Leveraging uncertainty information from deep neural networks for disease detection.Scientific Reports, 7(1):1–14, 2017.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Leveraging uncertainty information from deep neural networks for disease detection.Scientific Reports, 7(1):1–14, 2017

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This paper cites Uncertainty estimation in deep neural networks for dermoscopic image classification.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Uncertainty estimation in deep neural networks for dermoscopic image classification

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Unresolved cited work

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This paper cites Neal.Bayesian Learning for Neural Networks, volume 118 ofLecture Notes in Statistics.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Neal.Bayesian Learning for Neural Networks, volume 118 ofLecture Notes in Statistics

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This paper cites Dropout as a Bayesian approximation: Representing model uncertainty in deep learning.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Dropout as a Bayesian approximation: Representing model uncertainty in deep learning

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This paper cites Weight uncertainty in neural networks.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Weight uncertainty in neural networks

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This paper cites Practical variational inference for neural networks.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Practical variational inference for neural networks

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This paper cites Concrete dropout.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Concrete dropout

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Observation 0a419a61-0f5e-4cbb-9be7-347d85bbe7f1 · outbound

This paper cites Uncertainty estimation in medical image classification: systematic review.JMIR Medical Informatics, 10(8):e36427, 2022.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Uncertainty estimation in medical image classification: systematic review.JMIR Medical Informatics, 10(8):e36427, 2022

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This paper cites Can your ai differentiate cats from covid-19? sample efficient uncertainty estimation for deep learning safety.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Can your ai differentiate cats from covid-19? sample efficient uncertainty estimation for deep learning safety

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This paper cites Improving model calibration with accuracy versus uncertainty optimiza- tion.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Improving model calibration with accuracy versus uncertainty optimiza- tion

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This paper cites Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases

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Observation 2a76902e-5f6a-45be-b027-7b62ade7bae9 · outbound

This paper cites Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison

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Observation 6a792b8a-00e9-408b-82d2-ff9b7a327dc3 · outbound

This paper cites Deep transfer learning models for medical diabetic retinopathy detection.Acta Informatica Medica, 27(5):327, 2019.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Deep transfer learning models for medical diabetic retinopathy detection.Acta Informatica Medica, 27(5):327, 2019

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This paper cites The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific Data, 5(1):180161, 2018.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific Data, 5(1):180161, 2018

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This paper cites Skin lesion classification and detection using machine learning techniques: A systematic review.Diagnostics, 13(19):3147, 2023.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Skin lesion classification and detection using machine learning techniques: A systematic review.Diagnostics, 13(19):3147, 2023

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Observation 33e0ff5e-4f5c-4509-8c72-2de75fe04403 · outbound

This paper cites Unreliable Monte Carlo dropout uncertainty estimation.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Unreliable Monte Carlo dropout uncertainty estimation

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Observation a3337334-b764-4548-a028-9e4117500221 · outbound

This paper cites Variational dropout and the local reparameterization trick.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Variational dropout and the local reparameterization trick

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This paper cites Well-calibrated model uncertainty with temperature scaling for dropout variational inference.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Well-calibrated model uncertainty with temperature scaling for dropout variational inference

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Observation 725f951b-352a-4630-9f33-279787a38a32 · outbound

This paper cites Calibration of Model Uncertainty for Dropout Variational Inference.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Calibration of Model Uncertainty for Dropout Variational Inference

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This paper cites Staib, and John A.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Staib, and John A

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This paper cites Dropout injection at test time for post hoc uncertainty quantification in neural networks.Information Sciences, 645:119356, 2023.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Dropout injection at test time for post hoc uncertainty quantification in neural networks.Information Sciences, 645:119356, 2023

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This paper cites Can you trust your model’s uncertainty? Evaluating predictive uncertainty under dataset shift.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Can you trust your model’s uncertainty? Evaluating predictive uncertainty under dataset shift

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This paper cites 'In-Between' Uncertainty in Bayesian Neural Networks.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis 'In-Between' Uncertainty in Bayesian Neural Networks

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Radial Bayesian neural networks: Beyond discrete support in large-scale Bayesian deep learning

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This paper cites How good is the bayes posterior in deep neural networks really? InInternational Conference on Machine Learning (ICML), pages 10248–10259, 2020.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis How good is the bayes posterior in deep neural networks really? InInternational Conference on Machine Learning (ICML), pages 10248–10259, 2020

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This paper cites Soft calibration objectives for neural networks.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Soft calibration objectives for neural networks

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This paper cites Well-calibrated regression uncer- tainty in medical imaging with deep learning.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Well-calibrated regression uncer- tainty in medical imaging with deep learning

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Unresolved cited work

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Hinton and Drew van Camp

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Simple and scalable predictive uncertainty estimation using deep ensembles

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis A baseline for detecting misclassified and out-of-distribution examples in neural networks

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis The role of chest radiography in confirming covid-19 pneumonia.BMJ, 370:m2426, 2020

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Automated detection of covid-19 cases using deep neural networks with x-ray images.Computers in Biology and Medicine, 121:103792, 2020

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Distance-based detection of out-of-distribution silent failures for covid-19 lung lesion segmentation.Medical Image Analysis, 82:102596, 2022

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports.Scientific Data, 6:317, 2019

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Covid-net: a tailored deep convolutional neural network design for detection of covid-19 cases from chest x-ray images.Scientific Reports, 10(1):19549, 2020

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Covid-19 chest x-ray dataset initiative

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Actualmed covid-19 chest x-ray dataset initiative

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Rsna pneumonia detection challenge dataset

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Saborit, Joaquim Á

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Stony brook university covid-19 positive cases (covid-19-ny-sbu).https://doi.org/10.7937/TCIA.BBAG-2923, 2021

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Analysis of the clever hans effect in covid-19 detection using chest x-ray images and bayesian deep learning.Biomedical Signal Processing and Control, 90:105831, 2024

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis OpenOOD v1.5: Enhanced benchmark for out-of-distribution detection.Journal of Data-centric Machine Learning Research, 2, 2024

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Learning Confidence for Out-of-Distribution Detection in Neural Networks

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Unresolved cited work

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis On the Use of Mahalanobis Distance for Out-of-distribution Detection with Neural Networks for Medical Imaging

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Kernel PCA for out-of-distribution detection

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Alshalali, and Zaffar Ahmed Shaikh

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis APTOS 2019 blindness detection.https://www.kaggle.com/c/a ptos2019-blindness-detection, 2019

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Diabetic retinopathy 224x224 gaussian filtered

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Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis PhD thesis, University of Cambridge, 2016

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Observation 2e9c7202-f8d9-4328-acb0-356cfa5ddf1e · outbound

This paper cites Automatic detection and classification of diabetic retinopathy using the improved pooling function in the convolution neural network.Diagnostics, 13(15):2606, 2023.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Automatic detection and classification of diabetic retinopathy using the improved pooling function in the convolution neural network.Diagnostics, 13(15):2606, 2023

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-03T00:02:03.869593Z

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Observation 54819b59-4ddc-423f-a119-72eb69504a43 · outbound

This paper cites Alwakid, W.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Alwakid, W

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T00:02:03.872317Z

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Observation 19a95593-839d-42bd-b4f0-298f1edf129c · outbound

This paper cites Analysis of pre-trained convolutional neural network models in diabetic retinopathy detection through retinal fundus images.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Analysis of pre-trained convolutional neural network models in diabetic retinopathy detection through retinal fundus images

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-03T00:02:03.874887Z

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Observation 0d963b91-828a-48ab-a780-f420b21a02ef · outbound

This paper cites Dynamically weighted balanced loss: Class imbalanced learning and confidence calibration of deep neural networks.Diagnostics, 11(8):1242, 2021.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Dynamically weighted balanced loss: Class imbalanced learning and confidence calibration of deep neural networks.Diagnostics, 11(8):1242, 2021

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-03T00:02:03.877548Z

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Observation 703f0bd1-38f2-4267-bc1c-97b2ff6e1f63 · outbound

This paper cites Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-03T00:02:03.879842Z

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Observation b1b9aba8-be8b-4a8a-a1d1-006239c547f0 · outbound

This paper cites Pre-train your loss: Easy bayesian transfer learning with informative priors.Advances in Neural Information Processing Systems, 35:27706–27715, 2022.

Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis Pre-train your loss: Easy bayesian transfer learning with informative priors.Advances in Neural Information Processing Systems, 35:27706–27715, 2022

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-03T00:02:03.882397Z

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