CNN Approach for Prediction of Covid-19 from X-Ray Images
Poonam Patil , Rujul Modi , Harshita Jagtap, Damini Jadhav
DOI : 10.46335/IJIES.2023.8.4.5
Abstract – COVID-19 also referred to as Severe Acute Respiratory Syndrome Corona virus-2 (SARS-CoV-2) is a very contagious virus infection and has huge effect on global health. The virus is spread from infected person who talks, sneeze, or cough. The most standard method for diagnosing COVID-19 is RT-PCR, performing RT-PCR to detect COVID might be risky, but the X-rays are easiest way available used for detecting infections in the lungs. Using Artificial Intelligence (AI) techniques and convolutional neural networks (CNNs) have achieved fruitful results in medical image analysis and classification. This study suggests a CNN model using TensorFlow for analysing chest X-rays to predict COVID-19 pictures. The study follows a flexible method of deep learning utilizing the CNN model for detection and prediction if a patient is impacted or not with the disease employing image of a chest X-ray. The trained model produced using TensorFlow achieved anaccuracy rate of 97% during the performance training.
