COVID 19 Patient

Research on COVID-19 patients focuses on predicting disease severity and the need for hospitalization, particularly in vulnerable populations like children. This involves developing machine learning models, including dynamic Bayesian networks, neural networks, and graph neural networks, to analyze patient data (vital signs, blood tests, medical history) and forecast disease progression. These predictive models aim to optimize resource allocation in healthcare systems and improve patient outcomes by enabling timely interventions. The accuracy and interpretability of these models are key areas of ongoing investigation, with a focus on incorporating medical knowledge to enhance predictive power.