A Novel Ensemble-Based Machine Learning Algorithm to Predict the Conversion From Mild Cognitive Impairment to Alzheimer's Disease Using Socio-Demographic Characteristics, Clinical Information, and Neuropsychological Measures

Alzheimer's Disease Neuroimaging Initiative

doi:10.3389/fneur.2019.00756

A Novel Ensemble-Based Machine Learning Algorithm to Predict the Conversion From Mild Cognitive Impairment to Alzheimer's Disease Using Socio-Demographic Characteristics, Clinical Information, and Neuropsychological Measures

Alzheimer's Disease Neuroimaging Initiative

Research output: Contribution to journal › Article › Academic › peer-review

Original language	English
Article number	756
Number of pages	15
Journal	Frontiers in Neurology
Volume	10
DOIs	https://doi.org/10.3389/fneur.2019.00756
Publication status	Published - 16 Jul 2019

Keywords

Alzheimer's disease
clinical prediction rule
machine learning
mild cognitive impairment
personalized medicine
precision medicine
neuropsychological tests
OLDER-ADULTS
DEMENTIA
INDIVIDUALS
MRI
MCI
STATE
RISK

Access to Document

10.3389/fneur.2019.00756

Cite this

Alzheimer's Disease Neuroimaging Initiative (2019). A Novel Ensemble-Based Machine Learning Algorithm to Predict the Conversion From Mild Cognitive Impairment to Alzheimer's Disease Using Socio-Demographic Characteristics, Clinical Information, and Neuropsychological Measures. Frontiers in Neurology, 10, [756]. https://doi.org/10.3389/fneur.2019.00756

@article{32370a93a46941f9b938f69f6ec8082d,

title = "A Novel Ensemble-Based Machine Learning Algorithm to Predict the Conversion From Mild Cognitive Impairment to Alzheimer's Disease Using Socio-Demographic Characteristics, Clinical Information, and Neuropsychological Measures",

keywords = "Alzheimer's disease, clinical prediction rule, machine learning, mild cognitive impairment, personalized medicine, precision medicine, neuropsychological tests, OLDER-ADULTS, DEMENTIA, INDIVIDUALS, MRI, MCI, STATE, RISK",

author = "Massimiliano Grassi and Nadine Rouleaux and Daniela Caldirola and David Loewenstein and Koen Schruers and Giampaolo Perna and Michel Dumontier and {Alzheimer's Disease Neuroimaging Initiative}",

year = "2019",

month = jul,

day = "16",

doi = "10.3389/fneur.2019.00756",

language = "English",

volume = "10",

journal = "Frontiers in Neurology",

issn = "1664-2295",

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}

A Novel Ensemble-Based Machine Learning Algorithm to Predict the Conversion From Mild Cognitive Impairment to Alzheimer's Disease Using Socio-Demographic Characteristics, Clinical Information, and Neuropsychological Measures. / Alzheimer's Disease Neuroimaging Initiative.

In: Frontiers in Neurology, Vol. 10, 756, 16.07.2019.

Research output: Contribution to journal › Article › Academic › peer-review

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AU - Grassi, Massimiliano

AU - Rouleaux, Nadine

AU - Caldirola, Daniela

AU - Loewenstein, David

AU - Schruers, Koen

AU - Perna, Giampaolo

AU - Dumontier, Michel

AU - Alzheimer's Disease Neuroimaging Initiative

PY - 2019/7/16

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KW - clinical prediction rule

KW - machine learning

KW - mild cognitive impairment

KW - personalized medicine

KW - precision medicine

KW - neuropsychological tests

KW - OLDER-ADULTS

KW - DEMENTIA

KW - INDIVIDUALS

KW - MRI

KW - MCI

KW - STATE

KW - RISK

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DO - 10.3389/fneur.2019.00756

M3 - Article

VL - 10

JO - Frontiers in Neurology

JF - Frontiers in Neurology

SN - 1664-2295

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ER -