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Generalizability of Deep Learning Tuberculosis Classifier to COVID-19 Chest Radiographs: New Tricks for an Old Algorithm?

作者信息

Yi Paul H, Kim Tae Kyung, Lin Cheng Ting

机构信息

Radiology AI Lab (RAIL), Malone Center for Engineering in Healthcare, Johns Hopkins University Whiting School of Engineering.

The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD.

出版信息

J Thorac Imaging. 2020 Jul;35(4):W102-W104. doi: 10.1097/RTI.0000000000000532.

DOI:10.1097/RTI.0000000000000532
PMID:32427650
Abstract
摘要

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[2]
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[3]
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[8]
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[9]
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[10]
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[2]
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Digit Health. 2024-2-22

[3]
Combating COVID-19 Crisis using Artificial Intelligence (AI) Based Approach: Systematic Review.

Curr Top Med Chem. 2024

[4]
Harnessing Machine Learning in Early COVID-19 Detection and Prognosis: A Comprehensive Systematic Review.

Cureus. 2023-5-1

[5]
The impact of COVID-19 on TB in Iran: An illustrative study.

J Clin Tuberc Other Mycobact Dis. 2023-5

[6]
COVID-19 Detection: A Systematic Review of Machine and Deep Learning-Based Approaches Utilizing Chest X-Rays and CT Scans.

Cognit Comput. 2022-12-29

[7]
Calibrated bagging deep learning for image semantic segmentation: A case study on COVID-19 chest X-ray image.

PLoS One. 2022

[8]
Machine learning in the loop for tuberculosis diagnosis support.

Front Public Health. 2022

[9]
Supervised and weakly supervised deep learning models for COVID-19 CT diagnosis: A systematic review.

Comput Methods Programs Biomed. 2022-5

[10]
Explainable Machine Learning for COVID-19 Pneumonia Classification With Texture-Based Features Extraction in Chest Radiography.

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