MobApp4InfectiousDisease: Classify COVID-19, Pneumonia, and Tuberculosis

Illness due to infectious diseases has been always a global threat. Millions of people die per year due to COVID-19, pneumonia, and Tuberculosis (TB) as all of them infect the lungs. For all cases, early screening/diagnosis can help provide opportunities for better care. To handle this, we develop a...

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Bibliographic Details
Main Authors: Mahbub, Md. Kawsher, Hossain Zamil, Md. Zakir, Mozid Miah, Md. Abdul, Ghose, Partho, Biswas, Milon, Santosh, KC
Format: Conference Proceeding
Language:English
Subjects:
CNN
COVID-19
Infectious Disease
Lung
Mobile App
Neural networks
pneumonia
Pulmonary diseases
Sensitivity
Transfer learning
Tuberculosis
Online Access:Request full text
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Summary:Illness due to infectious diseases has been always a global threat. Millions of people die per year due to COVID-19, pneumonia, and Tuberculosis (TB) as all of them infect the lungs. For all cases, early screening/diagnosis can help provide opportunities for better care. To handle this, we develop an application, which we call MobApp4InfectiousDisease that can identify abnormalities due to COVID-19, pneumonia, and TB using Chest X-ray image. In our MobApp4InfectiousDisease, we implemented a customized deep network with a single transfer learning technique. For validation, we offered in-depth experimental study and we achieved, for COVID-19-pneumonia-TB cases, accuracy of 97.72%196.62%199.75%, precision of 92.72%1100.0%199.29%, recall of 98.89%188.54%199.65%, and F1-score of 95.00%194.00%199.00%. Our results are compared with state-of-the-art techniques. To the best of our knowl-edge, this is the first time we deployed our proof-of-the-concept MobApp4InfectiousDisease for a multi-class infec-tious disease classification.
ISSN:2372-9198
DOI:10.1109/CBMS55023.2022.00028