Formulation of an Elegant Diagnostic Approach for an Intelligent Disease Recommendation System

Kamra, Vikas; Kumar, Praveen; Mohammadian, Masoud

doi:10.1109/confluence.2019.8776952

Cited by 7 publications

(2 citation statements)

References 14 publications

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“…Panwar et al [29] propose an nCOVnet deep learning model for fast prediction of COVID-19 using CXR. Kamra et al [30] offer a deep learning-assisted method for early detection of COVID-19 using a dataset containing 286 CXR images by evaluating eight CNN out of which ResNET-34 gave the highest accuracy, 98.33%.…”

Section: Literature Reviewmentioning

confidence: 99%

Deep learning based COVID and Pneumonia detection using chest X-ray

Kumar,

Rakhimzhanova,

Rawat

et al. 2024

IJEECS

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<p class="Abstract">Since the outbreak, the novel coronavirus (COVID-19) has infected more than 180 million people and has taken a toll of 3.91 million lives globally as of June 2021. This virus causes symptoms like fever, cold, and fatigue, and can develop into Pneumonia which can be detected using chest X-rays (CXRs). Therefore, early detection of COVID-19 can help get early medical attention. However, a sudden rise in the number of cases in many countries caused by COVID waves increases the burden on their testing facilities. As a result, they sometimes fail to perform enough testing to contain the spread. This work proposes a deep learning model to detect COVID-19 and Pneumonia based on CXRs. The dataset for our COVID model contains a total of 3,400 CXRs images of COVID-19 patients and 3,400 normal CXRs. The dataset for our Pneumonia model contains 1,300 CXR images of Pneumonia patients and 1,300 normal CXRs. We use convolutional neural network provided by TensorFlow to build our model, which gave 94.17% and 93.55% accuracy for COVID model and Pneumonia model, respectively. Finally, we deployed our model on the web and added a web tracker, which gives us the cases, deaths, and recoveries state-wise and nationwide.</p>

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Section: Literature Reviewmentioning

confidence: 99%

Deep learning based COVID and Pneumonia detection using chest X-ray

Kumar,

Rakhimzhanova,

Rawat

et al. 2024

IJEECS

View full text Add to dashboard Cite

show abstract

“…In 2019, Kamra et al [21] provided a brief assessment of the literature based on various machine learning and data mining approaches used in medical diagnosis assistance systems. They found that smart healthcare applications linked to the developed systems would grow in popularity.…”

Section: Literature Reviewmentioning

confidence: 99%