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BSMHM2: Bayesian Semiparametric Mixed Hidden Markov Models for Delineating the Pathology of Alzheimer’s Disease
Alzheimer’s disease (AD) is a firmly incurable and progressive disease. The pathology of AD usually evolves from cognitive normal (CN), to mild cognitive impairment (MCI), to AD. The aim of this paper is to develop a Bayesian semiparametric mixed hidden Markov modeling (BSMHM2) framework to characte...
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| I publikationen: | Stat Methods Med Res |
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| Huvudupphovsmän: | , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
2017
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5984196/ https://ncbi.nlm.nih.gov/pubmed/29278101 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1177/0962280217748675 |
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