Data integration in Neuroscience

One of the primary challenges in neuroscience is the early diagnosis of neurodegenerative diseases (NDs). NDs are multifactorial diseases that are particularly difficult to diagnose in their early stages when symptoms are not yet evident. Pathological brain changes can occur over several decades before symptoms manifest. Achieving an earlier clinical diagnosis and effective management of NDs requires integrating multiple data sources, including genetic characteristics, clinical conditions, and environmental factors such as education level and lifestyle. 

This work aims at studying machine and deep learning models to combine different data modalities to improve the diagnosis performance.

Partner: University of Brescia - Department of Molecular and Translational Medicine.