Abstract #3053

Multimodal deep learning for Alzheimer’s disease classification and clinical score prediction

Vaibhavi Sanjeet Itkyal¹, Ishaan Batta², Anees Abrol³, and Vince Calhoun²

¹Neuroscience, Emory University, Decatur, GA, United States, ²Georgia Tech, Decatur, GA, United States, ³Georgia State University, Decatur, GA, United States

Synopsis

Keywords: Alzheimer's Disease, Multimodal, Neurodegeneration, Deep LearningIn this project, we use different neuroimaging modalities in the ADNI data, including structural magnetic resonance imaging (sMRI) and temporal transformations of resting-state functional magnetic resonance imaging (rs-fMRI) data, for several classification (e.g., diagnosis) and regression (e.g., age and clinical assessments) objectives.

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