NIH R01 · 2025
In the US, ~24 million persons live with COPD, half undiagnosed, and ~150,000 die of COPD annually. COPD causes over 700,000 US hospitalizations and costs nearly $50 billion per year. The human and financial burdens of COPD could likely be reduced if disease progression and other adverse events could be anticipated, enabling caregivers to focus finite resources on at-risk patients. We propose to create a decision-support tool that integrates biomedical informatics with advanced machine learning (ML) and deep learning (DL) algorithms to predict acute and chronic healthcare encounters (hospital admissions, readmissions, and ED encounters) and major disease progression events (home oxygen…
From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.