Multimodal autism detection: Deep hybrid model with improved feature level fusion.
Journal:
Computer methods and programs in biomedicine
Published Date:
Dec 18, 2024
Abstract
OBJECTIVE: Social communication difficulties are a characteristic of autism spectrum disorder (ASD), a neurodevelopmental condition. The earlier method of diagnosing autism largely relied on error-prone behavioral observation of symptoms. More intelligence approaches are in progress to diagnose the disorder, which still demands improvement in prediction accuracy. Furthermore, computer-aided design systems based on machine learning algorithms are extremely time-consuming and difficult to design. This study used deep learning techniques to develop a novel autism detection model in order to overcome these problems.