From pattern classification to stratification: towards conceptualizing the heterogeneity of Autism Spectrum Disorder.
Autism spectrum disorder
Biotypes
Classification
Clustering
Machine learning
Pattern recognition
Precision medicine
Stratification
Journal
Neuroscience and biobehavioral reviews
ISSN: 1873-7528
Titre abrégé: Neurosci Biobehav Rev
Pays: United States
ID NLM: 7806090
Informations de publication
Date de publication:
09 2019
09 2019
Historique:
received:
15
04
2019
revised:
10
07
2019
accepted:
15
07
2019
pubmed:
23
7
2019
medline:
17
3
2020
entrez:
23
7
2019
Statut:
ppublish
Résumé
Pattern classification and stratification approaches have increasingly been used in research on Autism Spectrum Disorder (ASD) over the last ten years with the goal of translation towards clinical applicability. Here, we present an extensive scoping literature review on those two approaches. We screened a total of 635 studies, of which 57 pattern classification and 19 stratification studies were included. We observed large variance across pattern classification studies in terms of predictive performance from about 60% to 98% accuracy, which is among other factors likely linked to sampling bias, different validation procedures across studies, the heterogeneity of ASD and differences in data quality. Stratification studies were less prevalent with only two studies reporting replications and just a few showing external validation. While some identified strata based on cognition and intelligence reappear across studies, biology as a stratification marker is clearly underexplored. In summary, mapping biological differences at the level of the individual with ASD is a major challenge for the field now. Conceptualizing those mappings and individual trajectories that lead to the diagnosis of ASD, will become a major challenge in the near future.
Identifiants
pubmed: 31330196
pii: S0149-7634(19)30319-7
doi: 10.1016/j.neubiorev.2019.07.010
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
240-254Subventions
Organisme : Medical Research Council
ID : MR/N026063/1
Pays : United Kingdom
Informations de copyright
Copyright © 2019 Elsevier Ltd. All rights reserved.