Deep Learning Approaches to Multimodal Prediction of Alzheimer’s Disease Pathology

Faculty of Electrical  Engineering of K.N.Toosi University of Technology holds the ” Deep Learning Approaches to Multimodal Prediction of Alzheimer’s Disease Pathology” lecture on Monday, October 27rd, at 13:00 PM by Dr. Jafar Zamani, Postdoctoral Researcher of Stanford University of USA.

Alzheimer’s disease develops silently in the brain years before symptoms appear. Neuroimaging with PET and MRI provides powerful tools to detect amyloid and tau, the hallmarks of AD pathology, but analyzing such complex data requires more than traditional methods. In this talk, I will present deep learning approaches that combine multiple neuroimaging modalities to predict AD pathology and track disease progression. This work demonstrates how AI can push the boundaries of neuroimaging, offering new opportunities for earlier detection and more precise monitoring of Alzheimer’s disease.

This lecture will be conducted in person; however, interested participants may also join virtually via the link provided below:

Location: The meeting room of Electrical  Engineering Faculty .