Digital postdoc start-up grant: P-AMyLo: Development of a Machine Learning-Based Diagnostic Score for Cardiac Amyloidosis Using Proteomics, Imaging, and Clinical Data

The P-AMyLo project aims to develop a new, simple, non-invasive diagnostic tool to help identify people at risk of developing cardiac amyloidosis, before the disease progresses. Using data sets from large health longitudinal studies in the UK and Germany, P-AMyLo will assess proteins in the blood of apparently healthy volunteers and link them to a later diagnosis of the disease at a clinical stage. Machine learning will be used to find the most important protein patterns that could signal cardiac amyloidosis's presence and early development.