Literature DB >> 29581008

Editorial on special issue: Machine learning on MCI.

Alessia Sarica1, Antonio Cerasa2, Aldo Quattrone3, Vince Calhoun4.   

Abstract

Mesh：

Year:  2018        PMID： 29581008     DOI： 10.1016/j.jneumeth.2018.03.011

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN： 0165-0270            Impact factor:   2.390


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  6 in total

1.  Towards Algorithmic Analytics for Large-scale Datasets.

Authors:  Danilo Bzdok; Thomas E Nichols; Stephen M Smith
Journal:  Nat Mach Intell       Date:  2019-07-09

2.  Deep residual learning for neuroimaging: An application to predict progression to Alzheimer's disease.

Authors:  Anees Abrol; Manish Bhattarai; Alex Fedorov; Yuhui Du; Sergey Plis; Vince Calhoun
Journal:  J Neurosci Methods       Date:  2020-04-08       Impact factor: 2.390

3.  To Explore the Predictive Power of Visuomotor Network Dysfunctions in Mild Cognitive Impairment and Alzheimer's Disease.

Authors:  Justine Staal; Francesco Mattace-Raso; Hennie A M Daniels; Johannes van der Steen; Johan J M Pel
Journal:  Front Neurosci       Date:  2021-06-28       Impact factor: 4.677

4.  TADPOLE Challenge: Accurate Alzheimer's disease prediction through crowdsourced forecasting of future data.

Authors:  Răzvan V Marinescu; Neil P Oxtoby; Alexandra L Young; Esther E Bron; Arthur W Toga; Michael W Weiner; Frederik Barkhof; Nick C Fox; Polina Golland; Stefan Klein; Daniel C Alexander
Journal:  Predict Intell Med       Date:  2019-10-10

5.  Random forest prediction of Alzheimer's disease using pairwise selection from time series data.

Authors:  P J Moore; T J Lyons; J Gallacher
Journal:  PLoS One       Date:  2019-02-14       Impact factor: 3.240

6.  Using path signatures to predict a diagnosis of Alzheimer's disease.

Authors:  P J Moore; T J Lyons; J Gallacher
Journal:  PLoS One       Date:  2019-09-19       Impact factor: 3.240
  6 in total

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