Benchmarking machine learning models for late-onset alzheimer’s disease prediction from genomic data

Javier De Velasco Oriol; Edgar E. Vallejo; Karol Estrada; José Gerardo Taméz Peña; The Alzheimer’s Disease Neuroimaging Initiative; Alzheimers Dis Neuroimaging Initia

doi:10.1186/s12859-019-3158-x

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Benchmarking machine learning models for late-onset alzheimer’s disease prediction from genomic data

Journal article

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Peer reviewed

Benchmarking machine learning models for late-onset alzheimer’s disease prediction from genomic data

Javier De Velasco Oriol, Edgar E. Vallejo, Karol Estrada, José Gerardo Taméz Peña, The Alzheimer’s Disease Neuroimaging Initiative and Alzheimers Dis Neuroimaging Initia

BMC bioinformatics, Vol.20(1), pp.709-717

12/16/2019

DOI: https://doi.org/10.1186/s12859-019-3158-x

PMID: 31842725

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Title: Benchmarking machine learning models for late-onset alzheimer’s disease prediction from genomic data
Creators: Javier De Velasco Oriol - Tecnológico de Monterrey
Edgar E. Vallejo - Tecnológico de Monterrey
Karol Estrada - Brandeis University, Rabb School of Continuing Studies, Division of Graduate Professional Studies
José Gerardo Taméz Peña - Monterrey, 64710 Mexico
The Alzheimer’s Disease Neuroimaging Initiative - Monterrey, 64710 Mexico
Alzheimers Dis Neuroimaging Initia
Publication Details: BMC bioinformatics, Vol.20(1), pp.709-717
Publisher: BioMed Central
Identifiers: 9924594038801921
Academic Unit: Rabb School of Continuing Studies, Division of Graduate Professional Studies
Language: English
Resource Type: Journal article

Benchmarking machine learning models for late-onset alzheimer’s disease prediction from genomic data

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