I’m excited to share our latest research, presented at the Explainable AI for Biomedical Images and Signals Special Session of the 32nd Italian Workshop on Neural Networks (WIRN 2024)! Our work focuses on the crucial role of the thalamus in Parkinson’s disease (PD) and how deviations between brain age and chronological age—known as the brain-age gap (BAG)—can offer insights into disease progression.

Using MRI scans and advanced Explainable Boosting Machines (EBM), we’ve developed a novel, interpretable machine learning model that accurately estimates BAG in PD patients. Our findings reveal a complex pattern of hypertrophy and atrophy in thalamic nuclei volumes in PD patients, highlighting specific nuclei as key predictors of brain age. This approach not only improves early diagnosis and prognosis but also opens doors to personalized treatment plans for those with Parkinson’s disease.

This research underscores the potential of combining neuroimaging with cutting-edge AI to enhance our understanding of neurological disorders. Stay tuned for more updates on how this could revolutionize PD diagnosis and treatment!

#ParkinsonsDisease #BrainHealth #AIinHealthcare #Neuroscience #MRI #MedicalResearch #WIRN2024

Attached the powerpoint presentation.