Applying Artificial Intelligence for Diagnostic Classification of Korean Autism Spectrum Disorder.

ABSTRACT:

Objective

The primary objective of this study was to predict subgroups of autism spectrum disorder (ASD) based on the Diagnostic Statistical Manual for Mental Disorders-IV Text Revision (DSM-IV-TR) by machine learning (ML). The secondary objective was to set up a ranking of Autism Diagnostic Interview-Revised (ADI-R) diagnostic algorithm items based on ML, and to confirm whether ML can sufficiently predict the diagnosis with these minimum items.

Methods

In the first experiment, a multiclass decision forest algorithm was applied, and the diagnostic algorithm score value of 1,269 Korean ADI-R test data was used for prediction. In the second experiment, we used 539 Korean ADI-R case data (over 48 months with verbal language) to apply mutual information to rank items used in the

SUBMITTER: Choi ES 

PROVIDER: S-EPMC7711119 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature