Sihang Jiang
Sihang Jiang is a PhD candidate at University of Virginia in systems engineering, and his research interests include Bayesian machine learning, Markov Chain Monte Carlo, AI for health, and natural language processing.
Sessions
In the era of big data, multi-modal data from multiple sources or modalities has become increasingly prevalent in various fields such as healthcare. The National COVID Cohort Collaborative (N3C) provides researchers with abundant clinical data in different forms by aggregating and harmonizing Electronic Health Records (EHR) data across different clinical organizations in the United States, making it convenient for researchers to analyze COVID-related topics and build models with large multimodal data. Bayesian risk analysis has advantages in handling the complexities and heterogeneities of multi-modal healthcare data, specifically in cohort studies when researchers try to answer questions of interest in public health or medicine field regarding COVID and Long COVID.