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Predicting Alzheimer's disease progression using multi-modal deep learning approach
2019
Scientific Reports
Alzheimer's disease (AD) is a progressive neurodegenerative condition marked by a decline in cognitive functions with no validated disease modifying treatment. It is critical for timely treatment to detect AD in its earlier stage before clinical manifestation. Mild cognitive impairment (MCI) is an intermediate stage between cognitively normal older adults and AD. To predict conversion from MCI to probable AD, we applied a deep learning approach, multimodal recurrent neural network. We developed
doi:10.1038/s41598-018-37769-z
pmid:30760848
pmcid:PMC6374429
fatcat:o4nlg7st3vh25dadt7yp3opguu