Minisymposium Presentation

This talk outlines the development of AI models for Risk Assessment and Disease Progression in Pandemic Preparedness. Leveraging advanced deep learning techniques, these models integrate diverse data sources like images, clinical features, and laboratory data to characterize disease subtypes and personalize risk assessment. Such AI-driven Clinical Risk Assessment aids healthcare professionals in resource allocation, especially in high-demand scenarios such as the COVID-19 pandemic.The talk will further demonstrate a specific AI model from an SNSF-funded research project focused on the development of an AI-multiomics-based prognostic stratification of acute and chronic COVID-19 patients. Using chest CT scans and clinical data, two models, AssessNet-19 and ChronRisk-19, significantly enhance severity assessment and long-COVID prediction. Evaluated on diverse patient cohorts, the models outperform radiologists and single-class lesion models. The research underscores the potential of AI in improving COVID-19 patient care, offering insights for future clinical workflows.