A Gaussian-based model for early detection of mild cognitive impairment using multimodal neuroimaging Article

Forouzannezhad, Parisa, Abbaspour, Alireza, Li, Chunfei et al. (2020). A Gaussian-based model for early detection of mild cognitive impairment using multimodal neuroimaging . JOURNAL OF NEUROSCIENCE METHODS, 333 10.1016/j.jneumeth.2019.108544

Open Access

cited authors

  • Forouzannezhad, Parisa; Abbaspour, Alireza; Li, Chunfei; Fang, Chen; Williams, Ulyana; Cabrerizo, Mercedes; Barreto, Armando; Andrian, Jean; Rishe, Naphtali; Curiel, Rosie E; Loewenstein, David; Duara, Ranjan; Adjouadi, Malek

sustainable development goals

authors

publication date

  • March 1, 2020

published in

keywords

  • ALZHEIMERS-DISEASE
  • Alzheimer's disease
  • BAYESIAN CLASSIFICATION
  • Biochemical Research Methods
  • Biochemistry & Molecular Biology
  • DEMENTIA
  • EARLY-DIAGNOSIS
  • Early Mild Cognitive Impairment (EMCI)
  • FDG-PET
  • FEATURE-SELECTION
  • FUNCTIONAL CONNECTIVITY NETWORKS
  • Gaussian Process
  • Life Sciences & Biomedicine
  • MCI
  • Multimodal Neuroimaging
  • Neurosciences
  • Neurosciences & Neurology
  • PREDICTION
  • Random Forest
  • STRUCTURAL MRI
  • Science & Technology

Digital Object Identifier (DOI)

publisher

  • ELSEVIER

volume

  • 333