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Principal Investigator  
Principal Investigator's Name: Alex Berg
Institution: Massachusetts Institute of Technology
Department: Electrical Engineering and Computer Science
Proposed Analysis: Alzheimer's Disease (AD) is believed to consist of several subtypes. Identifying these subtypes -and their distinct neuroimaging, genomic, and cellular features- may be the key to targeted clinical intervention. Overall, our group aims to identify granular subtypes of AD through imaging genetics and representation learning. Firstly, based on the work of Zhou et al (2019), we aim to train a convolutional neural network (CNN)-based classifier to predict patients' AD-status from MRI images. Then, using the trained CNN's internal feature representations, we aim to project patients' MRI data to low-dimensional representations and perform fuzzy k-means clustering - each resulting cluster representing a possible AD subtype. Finally, validation of these possible subtypes will occur through sparse canonical correlation analysis (SCCA) of patient-level neuroimaging, genetic, and cognitive data. References: Zhou T, Thung KH, Zhu X, Shen D. Effective feature learning and fusion of multimodality data using stage-wise deep neural network for dementia diagnosis. Hum Brain Mapp. 2019 Feb 15;40(3):1001-1016. doi: 10.1002/hbm.24428. Epub 2018 Nov 1. PMID: 30381863; PMCID: PMC6865441.
Additional Investigators  
Investigator's Name: William Li
Proposed Analysis: Ditto
Investigator's Name: Neil Deshmukh
Proposed Analysis: Ditto