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White matter structure and derived network properties are used to predict the progression from mild cognitive impairment of older adults to Alzheimer’s disease

BMC Geriatrics(2024)10.1186/s12877-024-05293-7Source: DataRank Database

White matter structure and derived network properties are used to predict the progression from mild cognitive impairment of older adults to Alzheimer’s disease is a research paper published in BMC Geriatrics (2024). On theSindex it has a DataRank of 0. It has been cited 7 times.

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Enrichment:Funding (1 grants)OA: goldTopics (18)IDs (PubMed, PMC)Annotations (1)

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Authors (13)

Guangying Zheng ORCID,Mengmeng Hu ORCID,Zihan Zhang ORCID,Zhongyu Yuan ORCID,Yuyun Xu ORCID

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PubMed:39160467 PMC:PMC11331623

NIA NIH HHS

Grant: U01 AG024904

goldLicense: cc-by-nc-nd

publisherhttps://bmcgeriatr.biomedcentral.com/counter/pdf/10.1186/s12877-024-05293-7

publisherhttps://link.springer.com/content/pdf/10.1186/s12877-024-05293-7.pdf

publisherhttps://link.springer.com/article/10.1186/s12877-024-05293-7/fulltext.html

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/11331623

repositoryhttps://doaj.org/article/c29530e06b984735b456bb7abd2605d0

MeSH Terms

HumansAlzheimer DiseaseDisease ProgressionCohort StudiesPredictive Value of TestsAgedAged, 80 and overFemaleMaleDiffusion Tensor ImagingWhite MatterMachine LearningCognitive Dysfunction

Keywords

Alzheimer’s diseaseMachine LearningMild Cognitive ImpairmentDiffusion Tensor ImagingWhite Matter Microstructure

White matter structure and derived network properties are used to predict the progression from mild cognitive impairment of older adults to Alzheimer’s disease

FAIR Checklist

Authors (13)

Funding (1 grants)

Open Access

Topics

Annotations (Europe PMC)