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Covid Prediction from X-ray Images

D. Haritha, Ch. Praneeth, M. Krishna Pranathi

20202020 5th International Conference on Computing, Communication and Security (ICCCS)27 citationsDOIOpen Access PDF

Abstract

Early detection of COVID 19 is having the significant impact on curtailing the COVID 19 transmission at faster rate and is the need of the hour. An Artificial Intelligence diagnostic using Deep Learning models trained with X ray images of COVID infected and noninfected patients is a new promising method that helps in early prediction and identification of COVID infected persons. This paper `COVID prediction from X-ray images' acquaints a system to be utilized for automatic identification of corona virus from chest X-ray by machines in less time i.e. less than five minutes. For this we consider dataset of chest x-ray images of pneumonia, COVID 19 disease and normal infected people. We use the concept of Transfer Learning for its advantage of decreasing the training time for a neural network model. Using the VGG model of Transfer Learning we show an accuracy of 99.49% in prediction of the COVID 19 from X ray of the suspected patient.

Topics & Concepts

Coronavirus disease 2019 (COVID-19)Transfer of learningDeep learningComputer scienceArtificial intelligenceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Identification (biology)Artificial neural networkTransmission (telecommunications)2019-20 coronavirus outbreakPneumoniaPattern recognition (psychology)MedicineDiseaseVirologyPathologyTelecommunicationsInternal medicineOutbreakBiologyInfectious disease (medical specialty)BotanyCOVID-19 diagnosis using AIAI in cancer detectionRadiomics and Machine Learning in Medical Imaging