Efficient deep learning-based data-centric approach for autism spectrum disorder diagnosis from facial images using explainable AI

Alam, Mohammad Shafiul and Rashid, Muhammad Mahbubur and Faizabadi, Ahmed Rimaz and Mohd Zaki, Hasan Firdaus and Alam, Tasfiq E. and Ali, Md Shahin and Gupta, Kishor Datta and Ahsan, Md Manjurul (2023) Efficient deep learning-based data-centric approach for autism spectrum disorder diagnosis from facial images using explainable AI. Technologies, 11 (5). pp. 1-27. E-ISSN 2227-7080

	PDF - Published Version Restricted to Registered users only Download (28MB) | Request a copy
Preview	PDF - Supplemental Material Download (221kB) | Preview

Abstract

The research describes an effective deep learning-based, data-centric approach for diagnosing autism spectrum disorder from facial images. To classify ASD and non-ASD subjects, this method requires training a convolutional neural network using the facial image dataset. As a part of the data-centric approach, this research applies pre-processing and synthesizing of the training dataset. The trained model is subsequently evaluated on an independent test set in order to assess the performance matrices of various data-centric approaches. The results reveal that the proposed method that simultaneously applies the pre-processing and augmentation approach on the training dataset outperforms the recent works, achieving excellent 98.9% prediction accuracy, sensitivity, and specificity while having 99.9% AUC. This work enhances the clarity and comprehensibility of the algorithm by integrating explainable AI techniques, providing clinicians with valuable and interpretable insights into the decision-making process of the ASD diagnosis model.

Item Type:	Article (Journal)
Uncontrolled Keywords:	deep learning; convolutional neural network; ASD diagnosis; augmentation; facial image
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1501 Applied optics. Lasers T Technology > TA Engineering (General). Civil engineering (General) > TA329 Engineering mathematics. Engineering analysis
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Dr Muhammad Rashid
Date Deposited:	13 Sep 2023 15:14
Last Modified:	09 Feb 2024 16:46
URI:	http://irep.iium.edu.my/id/eprint/106526

Actions (login required)

View Item