Uncover This Tech Term: Uncertainty Quantification for Deep Learning-Reference-Cited by-同舟云学术

Uncover This Tech Term: Uncertainty Quantification for Deep Learning

Published:2024 Issue:4 Volume:25 Page:395
ISSN:1229-6929
Container-title:Korean Journal of Radiology
language:en
Short-container-title:Korean J Radiol

Author:

Faghani Shahriar¹^ORCID,Gamble Cooper¹^ORCID,Erickson Bradley J.¹^ORCID

Affiliation:

1. Artificial Intelligence Laboratory, Department of Radiology, Mayo Clinic, Rochester, MN, USA.

Publisher

XMLink

Link

https://kjronline.org/pdf/10.3348/kjr.2024.0108

Reference18 articles.

1. ChatGPT and Other Large Language Models Are Double-edged Swords

2. Quantifying Uncertainty in Deep Learning of Radiologic Images

3. On calibration of modern neural networks. accessed on January 1, 2024. Available at: http://proceedings.mlr.press/v70/guo17a.html

4. Conformal Prediction: A Gentle Introduction

5. Simple and scalable predictive uncertainty estimation using deep ensembles. accessed on January 1, 2024. Available at: https://proceedings.neurips.cc/paper_files/paper/2017/hash/9ef2ed4b7fd2c810847ffa5fa85bce38-Abstract.html

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1. Differentiation of glioblastoma from solitary brain metastasis using deep ensembles: Empirical estimation of uncertainty for clinical reliability;Computer Methods and Programs in Biomedicine;2024-09

2. Deep Conformal Supervision: a comparative study;2024-03-28

3. Caveats in Using Abnormality/Probability Scores from Artificial Intelligence Algorithms: Neither True Probability nor Level of Trustworthiness;Korean Journal of Radiology;2024