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MobApp4InfectiousDisease: Classify COVID-19, Pneumonia, and Tuberculosis

Md. Kawsher Mahbub, Md Zakir Hossain Zamil, Md. Abdul Mozid Miah, Partho Ghose, Milon Biswas, KC Santosh

202220 citationsDOI

Abstract

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.

Topics & Concepts

PneumoniaCoronavirus disease 2019 (COVID-19)TuberculosisMedicineTransfer of learningSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Artificial intelligenceComputer scienceBacterial pneumoniaInfectious disease (medical specialty)DiseaseInternal medicinePathologyCOVID-19 diagnosis using AIDigital Imaging for Blood DiseasesPneumonia and Respiratory Infections
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