Subtyping cognitive profiles in Autism Spectrum Disorder using a functional random forest
Feczko, Eric
2018

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Abstract

DSM-5 Autism Spectrum Disorder (ASD) comprises a set of neurodevelopmental disorders characterized by deficits in social communication and interaction and repetitive behaviors or restricted interests, and may both affect and be affected by multiple cognitive mechanisms. This study attempts to identify and characterize cognitive subtypes within the ASD population using a random forest (RF) machine learning classification model.

Details

Title
Subtyping cognitive profiles in Autism Spectrum Disorder using a functional random forest
Creator
Feczko, Eric : Oregon Health and Science University
Contributor
Fair, Damien Advisor (Oregon Health and Science University)
Publisher
Oregon Health and Science University
Date
2018-06-01
Subjects
Keywords
DOI
https://doi.org/10.6083/O41TPP
Content Type
Thesis
Degree Type
M.B.I.
Academic Program
Biomedical Informatics
Department
Department of Medical Informatics and Clinical Epidemiology
School
School of Medicine
Copyright Status
Record ID
7863
Record Created
2023-06-29
Record Appears in
Organizations > Departments and Divisions > School of Medicine Clinical Sciences Departments and Divisions > Department of Medical Informatics and Clinical Epidemiology
OHSU Works > Student Work > Degrees > Master in Biomedical Informatics (M.B.I.)
Organizations > Schools > School of Medicine
OHSU Works > Student Work > Theses
Biomedical Informatics
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