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A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI
In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM ar...
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| Publicado no: | Med Image Comput Comput Assist Interv |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2015
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4820012/ https://ncbi.nlm.nih.gov/pubmed/27054199 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-319-24553-9_70 |
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