National Heart, Lung, and Blood Institute 5R01HL157879-04

COPD SUBTYPES AND EARLY PREDICTION USING INTEGRATIVE PROBABILISTIC GRAPHICAL MODELS R01HL157879

The award funds the development of computational methods to subtype COPD using multi-scale data, aiming to improve disease understanding and prediction.

Description

This project focuses on developing computational methods based on probabilistic graphical models (PGMs) to address the unmet need for robust disease subtyping using multi-scale data (omics, chest CT, clinical). The objectives include building a comprehensive framework for disease subclassification, identifying stable COPD subtypes longitudinally, and creating interpretable models of the disease. Deliverables include new approaches for clinical subtyping, predictors of COPD progression, and valuable omics datasets.

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