AI-Driven Analysis of Pulmonary Hypertension: Enhancing Diagnosis and Patient Outcomes Using ASPIRE Registry Data

A doctor reviewing a lung scan for pulmonary hypertension currently relies on pattern recognition that artificial intelligence could sharpen. Pulmonary hypertension is a progressive disease where the lungs’ blood vessels narrow, forcing the heart to work harder. Early diagnosis improves outcomes, but current methods miss subtle signs or misclassify the condition. This project will train AI on thousands of patient records and images from the ASPIRE Registry, a large UK clinical database. The goal is to build tools that detect the disease earlier and classify its subtype more accurately than standard approaches. If the AI tools work, clinicians could make faster, more confident treatment decisions without waiting for specialist review. That could mean patients start targeted therapies sooner, slowing disease progression and reducing hospital admissions. The impact would be felt in routine NHS respiratory and cardiology clinics—not in dramatic breakthroughs, but in quieter, more consistent improvements to diagnostic accuracy. The project does not claim to cure pulmonary hypertension; it aims to make the existing diagnostic pathway more reliable and efficient.