Data for: MACHINE LEARNING IN MEDICINE: CLASSIFICATION AND PREDICTION OF DEMENTIA BY SUPPORT VECTOR MACHINES (SVM)

Published: 2 Jul 2019 | Version 1 | DOI: 10.17632/tsy6rbc5d4.1
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Description of this data

This set consists of a longitudinal collection of 150 subjects aged 60 to 96. Each subject was scanned on two or more visits, separated by at least one year for a total of 373 imaging sessions. For each subject, 3 or 4 individual T1-weighted MRI scans obtained in single scan sessions are included. The subjects are all right-handed and include both men and women. 72 of the subjects were characterized as nondemented throughout the study. 64 of the included subjects were characterized as demented at the time of their initial visits and remained so for subsequent scans, including 51 individuals with mild to moderate Alzheimer’s disease. Another 14 subjects were characterized as nondemented at the time of their initial visit and were subsequently characterized as demented at a later visit.

Experiment data files

This data is associated with the following publication:

Machine learning in medicine: Performance calculation of dementia prediction by support vector machines (SVM)

Published in: Informatics in Medicine Unlocked

Latest version

  • Version 1

    2019-07-02

    Published: 2019-07-02

    DOI: 10.17632/tsy6rbc5d4.1

    Cite this dataset

    Battineni, Gopi; Amenta, Francesco; Chintalapudi, Nalini (2019), “Data for: MACHINE LEARNING IN MEDICINE: CLASSIFICATION AND PREDICTION OF DEMENTIA BY SUPPORT VECTOR MACHINES (SVM)”, Mendeley Data, v1 http://dx.doi.org/10.17632/tsy6rbc5d4.1

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Categories

Artificial Intelligence, Machine Learning, Dementia Practice

Licence

CC BY NC 3.0 Learn more

The files associated with this dataset are licensed under a Attribution-NonCommercial 3.0 Unported licence.

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You are free to adapt, copy or redistribute the material, providing you attribute appropriately and do not use the material for commercial purposes.

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