Computer-aided autism diagnosis using visual attention models and eye-tracking: replication and improvement proposal.

ABSTRACT:

Background

Autism Spectrum Disorder (ASD) diagnosis can be aided by approaches based on eye-tracking signals. Recently, the feasibility of building Visual Attention Models (VAMs) from features extracted from visual stimuli and their use for classifying cases and controls has been demonstrated using Neural Networks and Support Vector Machines. The present work has three aims: 1) to evaluate whether the trained classifier from the previous study was generalist enough to classify new samples with a new stimulus; 2) to replicate the previously approach to train a new classifier with a new dataset; 3) to evaluate the performance of classifiers obtained by a new classification algorithm (Random Forest) using the previous and the current datasets.

Methods

The previously approach wa

SUBMITTER: Franco FO 

PROVIDER: S-EPMC10722824 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature