Early Detect of Covid-19 from Clinical Symptoms Based on Artificial Intelligence

Abstract

Pneumonia coronavirus disease 2019 (COVID-19) is an inflammation of the lung parenchyma caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).PCR and Swab are used in the first examination of Covid patients based on their clinical symptoms, and radiographic examination is used in the supporting examinations to confirm the diagnosis of Covid-19.Currently, the diagnosis of COVID-19 from clinical symptoms is made by the physician after reviewing the patient's medical history and performing a physical examination.Depending on the results, the diagnosis may be considered normal or the patient may be suspected of having COVID-19.Naturally, this process is less successful, and the diagnostic outcomes are subpar.The aim of the study was to develop a diagnostic application based on artificial intelligence for the early detection of Covid-19 from clinical symptoms.The method used for early detection of Covid-19 is the Back propagation Artificial Neural Network (JST) with Momentum.In order to stop the spread of COVID-19, it is intended that this software can improve doctors' accuracy in diagnosing the virus, act as a second opinion, and speed up the diagnosis process.

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