Early identification of mild cognitive impairment using incomplete random forest-robust support vector machine and FDG-PET imaging

Author:

Lu Shen,Xia Yong,Cai Weidong,Fulham Michael,Feng David Dagan

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shaanxi Province, China

Fundamental Research Funds for the Central Universities

Returned Overseas Scholar Project of Shaanxi Province, China

Alzheimer’s Disease Neuroimaging Initiative

National Institutes of Health

DOD ADNI

Department of Defense

National Institute on Aging

National Institute of Biomedical Imaging and Bioengineering

AbbVie

Alzheimer’s Association

Alzheimer’s Drug Discovery Foundation

Araclon Biotech

BioClinica, Inc.

Biogen

Bristol-Myers Squibb Company

CereSpir, Inc.

Cogstate

Eisai Inc.

Elan Pharmaceuticals, Inc.

Eli Lilly and Company

EuroImmun

F. Hoffmann-La Roche Ltd

Genentech, Inc.

Fujirebio

GE Healthcare

IXICO Ltd.

Janssen Alzheimer Immunotherapy Research & Development, LLC.

Johnson & Johnson Pharmaceutical Research & Development LLC.

Lumosity

Lundbeck

Merck & Co., Inc.

Meso Scale Diagnostics, LLC.

NeuroRx Research

Neurotrack Technologies

Novartis Pharmaceuticals Corporation

Pfizer Inc.

Piramal Imaging

Servier

Takeda Pharmaceutical Company

Transition Therapeutics

Canadian Institutes of Health Research

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference32 articles.

1. ADNI, 2016. http://adni.loni.usc.edu/methods/pet-analysis/pre-processing/.

2. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease;Albert;Alzheimer's Dement.,2011

3. Heterogeneity of brain glucose metabolism in mild cognitive impairment and clinical progression to alzheimer disease;Anchisi;Arch. Neurol.,2005

4. Manifold regularization: a geometric framework for learning from labeled and unlabeled examples;Belkin;J. Mach. Learn. Res.,2006

5. Robust convex optimization;Ben-Tal;Math. Oper. Res.,1998

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