Interpretable Machine Learning Reveals Dissimilarities Between Subtypes of Autism Spectrum Disorder

Interpretable Machine Learning Reveals Dissimilarities Between Subtypes of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a heterogeneous neuropsychiatric disorder with a complex genetic background. Analysis of altered molecular processes in ASD patients requires linear and nonlinear methods that provide interpretable solutions. Interpretable machine learning provides legible models th...

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Bibliographic Details
Main Authors: Mateusz Garbulowski, Karolina Smolinska, Klev Diamanti, Gang Pan, Khurram Maqbool, Lars Feuk, Jan Komorowski
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-02-01
Series:Frontiers in Genetics
Subjects:
autism spectrum disorder
interpretable machine learning
transcriptomics
rule-based classification
autism spectrum disorder subtypes
data integration
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2021.618277/full

Internet

https://www.frontiersin.org/articles/10.3389/fgene.2021.618277/full

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