Analysis Performance Of Image Processing Technique Its Application by Decision Support Systems On Covid-19 Disease Prediction Using Convolution Neural Network

The Covid-19 pandemic has been identified as a key issue for human society, in recent times. The presence of the infection on any human is identified according to different symptoms like cough, fever, headache, breathless and so on. However, most of the symptoms are shared by various other diseases, which makes it challenging for the medical practitioners to identify the infection. To aid the medical practitioners, there are a number of approaches designed which use different features like blood report, lung and cardiac features to detect the disease. The method captures the lung image using magnetic resonance imaging scan device and records the cardiac features. Using the image, the lung features are extracted and from the cardiac graph, the cardiac features are extracted. Similarly, from the blood samples, the features are extracted. By extracting such features from the person, the method estimates different weight measures to predict the disease. Different methods estimate the similarity of the samples in different ways to classify the input sample. However, the image processing techniques are used for different problems in medical domain;the same has been used in the detection of the disease. Also, the presence of Covid-19 is detected using different set of features by various approaches. [ FROM AUTHOR] Copyright of Computer Journal is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Analysis Performance Of Image Processing Technique Its Application by Decision Support Systems On Covid-19 Disease Prediction Using Convolution Neural Network

The Covid-19 pandemic has been identified as a key issue for human society, in recent times. The presence of the infection on any human is identified according to different symptoms like cough, fever, headache, breathless and so on. However, most of the symptoms are shared by various other diseases, which makes it challenging for the medical practitioners to identify the infection. To aid the medical practitioners, there are a number of approaches designed which use different features like blood report, lung and cardiac features to detect the disease. The method captures the lung image using magnetic resonance imaging scan device and records the cardiac features. Using the image, the lung features are extracted and from the cardiac graph, the cardiac features are extracted. Similarly, from the blood samples, the features are extracted. By extracting such features from the person, the method estimates different weight measures to predict the disease. Different methods estimate the similarity of the samples in different ways to classify the input sample. However, the image processing techniques are used for different problems in medical domain;the same has been used in the detection of the disease. Also, the presence of Covid-19 is detected using different set of features by various approaches.