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Prediction of Autism Risk From Family Medical History Data Using Machine Learning: A National Cohort Study From Denmark
Journal article   Open access   Peer reviewed

Prediction of Autism Risk From Family Medical History Data Using Machine Learning: A National Cohort Study From Denmark

Linda Ejlskov, Jesper N. Wulff, Amy Kalkbrenner, Christine Ladd-Acosta, M. Danielle Fallin, Esben Agerbo, Preben Bo Mortensen, Brian K. Lee and Diana Schendel
Biological psychiatry global open science, v 1(2), pp 156-164
05 May 2021
DOI: https://doi.org/10.1016/j.bpsgos.2021.04.007
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.1016/j.bpsgos.2021.04.007View
Published, Version of Record (VoR)CC BY-NC-ND V4.0,  Open

Abstract

Archival Report Autism Epidemiology Family history Machine learning Population based Risk score

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19 citations in Web of Science
26 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Neurosciences
Psychiatry
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