EfficientNet-Based Convolutional Neural Networks for Tuberculosis Classification-Reference-Cited by-同舟云学术

EfficientNet-Based Convolutional Neural Networks for Tuberculosis Classification

Published:2021 Issue: Volume: Page:227-244
ISSN:1568-2684
Container-title:Computational Biology
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Author:

Ravi Vinayakumar,Narasimhan Harini,Pham Tuan D.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-69951-2_9

Reference34 articles.

1. Fauci AS, Braunwald E, Kasper DL, Harrison TR (2009) Princípios de medicina interna, vol I. McGraw-Hill Interamericana, Madrid

2. Golub JE, Bur S, Cronin WA, Gange S, Baruch N, Comstock GW, Chaisson RE (2006) Delayed tuberculosis diagnosis and tuberculosis transmission. Int J Tuberc Lung Dis 10(1):24–30

3. World Health Organization (2019) Global tuberculosis report 2019. World Health Organization, Geneva

4. World Health Organization (2020) Global tuberculosis report 2020. World Health Organization, Geneva

5. Leung CC (2011) Reexamining the role of radiography in tuberculosis case finding. Int J Tuberc Lung Dis 15(10):1279

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