Data Mining-Based Model for Computer-Aided Diagnosis of Autism and Gelotophobia: Mixed Methods Deep Learning Approach.

ABSTRACT:

Background

Gelotophobia, the fear of being laughed at, is a social anxiety condition that affects approximately 6% of neurotypical individuals and up to 45% of those with autism spectrum disorder (ASD). This comorbidity can significantly impair the quality of life, particularly in adolescents with high-functioning ASD, where the prevalence reaches 41.98%. Accurate and automated detection tools could enhance early diagnosis and intervention.

Objective

This study aimed to develop a deep learning-based diagnostic system that integrates facial emotion recognition with validated questionnaires to detect gelotophobia in individuals with or without ASD.

Methods

The system was trained to identify ASD status using a balanced dataset of 2932 facial images (n=1466; 50% from indi

SUBMITTER: Eldawansy M 

PROVIDER: S-EPMC12391841 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature