Two papers at ML4H and the NeurIPS Time Series for Health workshop

Two papers led by Hongtao Hao were accepted and published in the Proceedings of Machine Learning Research, and presented as posters at ML4H 2025:

• Bayesian Event-Based Model for Disease Subtype and Stage Inference — inferring both which subtype of progression a patient follows and how far along it they are.
• Joint Progression Modeling (JPM): A Probabilistic Framework for Mixed-Pathology Progression — dropping the usual assumption that each patient has exactly one disease.

Both were also presented at the NeurIPS workshop on Learning from Time Series for Health. See the publications page for details, and the disease progression project for context.