Using Cross Entropy as a Performance Metric for Quantifying Uncertainty in DNN Image Classifiers: An Application to Classification of Lung Cancer on CT Images-Reference-Cited by-同舟云学术

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Using Cross Entropy as a Performance Metric for Quantifying Uncertainty in DNN Image Classifiers: An Application to Classification of Lung Cancer on CT Images

Published:2024 Issue:01 Volume:17 Page:1-12
ISSN:1937-6871
Container-title:Journal of Biomedical Science and Engineering
language:
Short-container-title:JBiSE

Author:

Matsuyama Eri,Nishiki Masayuki,Takahashi Noriyuki,Watanabe Haruyuki

Publisher

Scientific Research Publishing, Inc.

Reference34 articles.

1. Cancer statistics, 2023

2. Single-cell data analysis of malignant epithelial cell heterogeneity in lung adenocarcinoma for patient classification and prognosis prediction

3. Signaling pathways and targeted therapies in lung squamous cell carcinoma: mechanisms and clinical trials

4. Carcinome à grandes cellules, carcinome lymphoepithelioma-like, carcinome NUT

5. Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening

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