COVID 19 Severity

COVID-19 severity research aims to understand and predict the progression of the disease, enabling better patient management and resource allocation. Current efforts focus on developing machine learning models, particularly deep learning architectures like convolutional neural networks (CNNs) and ensemble methods, to analyze medical images (chest X-rays and CT scans) and patient data to classify disease severity. These models leverage various features, including radiomics from lung tissue and even epicardial adipose tissue, and incorporate techniques like contrastive mixup and Bayesian networks to improve accuracy and interpretability. Improved prediction of severity holds significant potential for optimizing clinical care and public health responses.