Prediction of Covid-19 symptoms with chest x-ray to optimize the solution through the MCOA Algorithm for feature extraction and measurement

Abstract

Due to poor understanding and inconsistent knowledge about covid-19 symptoms, the survival rate will decrease anywhere in the world. Every person who lives in the world should aware of COVID-19 symptoms to protect their life and hence increase the mortality rate of humans. The Indian government took precautions to lower the fatality rate, which includes hand sanitizer, wearing NS2 masks and keeping social distance to live a long life. The proposed method uses the MCOA-modified cat optimization algorithm to extract the image features and predict them in earlier stages and diagnosis. Furthermore, the proposed method clusters the chest image concerning size, shape and intensity concerning the irregular edges present in the chest imaging. The proposed MCAO algorithm cluster the chest image with an accuracy of about 95% and fit into the solution space with the state of art. The problem of the concave region present in the image is clustered in the solution space to delineate the parameters of pneumonia, fever, mucus fluid and respiration rate. The method gives the solution to the radiologist to detect earlier covid 19 symptoms for feature extraction and measurement.