Session

DescriptionTo address emerging virus variants, our strategy integrates next-gen vaccines and personalized disease treatments. In Bioinformatics Sequencing, HPC and AI power vaccine development and infection control. Simultaneously, AI-Driven Clinical Risk Assessment aids healthcare in pandemics. Personalized disease stratification involves AI models for risk assessment and interpretability-guided deep learning in medical applications. Standardizing EHR and Federated Learning ensures data integrity and privacy. In Bioinformatics Sequencing, we tackle challenges through: Drug Discovery for Next-Gen Vaccines: Applying bioinformatics to identify therapeutic candidates from genomic data for infectious diseases. Evolutionary Analysis for Infection Spread: Analyzing viral sequence data to identify important genes, functions, and evolution for minimizing and tracking infection spread. Accelerating Genotype-Phenotype Workflow: Correlating genotype to phenotype for efficient drug discovery in functional genomics. For AI-Driven Clinical Risk Assessment, methods include: AI Models for Disease Progression: Using advanced deep learning to characterize disease subtypes based on unsupervised and supervised learning. Interpretability-Guided Deep Learning: Enhancing comprehension in medical AI by addressing bias, shortcut learning, and susceptibility to attacks. Standardizing EHR and Federated Learning: Ensuring uniform Electronic Health Records (EHRs) usage, standardizing data formats, and addressing privacy concerns through federated learning. This minisymposium brings together experts to accelerate pandemic preparedness with clinico-genomic-data to improve diagnosis.