Covid Prediction using Machine Learning

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https://www.ijert.org/covid-predictio...
IJERTV10IS050205
Covid Prediction using Machine Learning

K. Nishitha , C. Shiny Gracy , B. Priyadharshini , M. Sowmiya , N. Kadhar Basha

Prediction of COVID is most challenging problem due to structure of LungNodule, where most of the cells are overlapped each other. An outbreak of a novelcorona virus disease (i.e., COVID-19) has been recorded in Wuhan, China since late December 2019, which subsequently became pandemic around the world. The onset of serious illness may result in death as a consequence of substantial alveolardamage and progressive respiratory failure. Although laboratory testing, e.g., usingreverse transcription polymerase chain reaction (RT-PCR), is the golden standard for clinical diagnosis, the tests may produce false negatives. Moreover, under thepandemic situation, shortage of RT-PCR testing resources may also delay the following clinical decision and treatment. Under such circumstances, chest CT imaging has become a valuable tool for both diagnosis and prognosis of COVID-19 patients. In this project, we propose a weakly supervised deep learning strategyfor detecting and classifying COVID-19 infection from CT images. The proposedmethod can minimize the requirements of manual labeling of CT images but stillbe able to obtain accurate infection detection and distinguish COVID-19 from non-covid cases.