Automated Autism Spectral Disorder Classification Using Optimal Machine Learning Model  

作　　者：Hanan Abdullah Mengash Hamed Alqahtani Mohammed Maray Mohamed K.Nour Radwa Marzouk Mohammed Abdullah Al-Hagery Heba Mohsen Mesfer Al Duhayyim 

机构地区：[1]Department of Information Systems,College of Computer and Information Sciences,Princess Nourah bint Abdulrahman University,P.O.Box 84428,Riyadh,11671,Saudi Arabia [2]Department of Information Systems,College of Computer Science,Center of Artificial Intelligence and Unit of Cybersecurity,King Khalid University,Abha,Saudi Arabia [3]Department of Information Systems,College of Computer Science,King Khalid University,Abha,Saudi Arabia [4]Department of Computer Sciences,College of Computing and Information System,Umm Al-Qura University,Saudi Arabia [5]Department of Computer Science,College of Computer,Qassim University,Saudi Arabia [6]Department of Computer Science,Faculty of Computers and Information Technology,Future University in Egypt,New Cairo,11835,Egypt [7]Department of Computer Science,College of Sciences and Humanities-Aflaj,Prince Sattam bin Abdulaziz University,Saudi Arabia

出　　处：《Computers, Materials & Continua》2023年第3期5251-5265,共15页计算机、材料和连续体（英文）

基　　金：The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Large Groups Project Under Grant Number(61/43);Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R114);Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia;The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:(22UQU4310373DSR26).

摘　　要：Autism Spectrum Disorder (ASD) refers to a neuro-disorder wherean individual has long-lasting effects on communication and interaction withothers.Advanced information technologywhich employs artificial intelligence(AI) model has assisted in early identify ASD by using pattern detection.Recent advances of AI models assist in the automated identification andclassification of ASD, which helps to reduce the severity of the disease.This study introduces an automated ASD classification using owl searchalgorithm with machine learning (ASDC-OSAML) model. The proposedASDC-OSAML model majorly focuses on the identification and classificationof ASD. To attain this, the presentedASDC-OSAML model follows minmaxnormalization approach as a pre-processing stage. Next, the owl searchalgorithm (OSA)-based feature selection (OSA-FS) model is used to derivefeature subsets. Then, beetle swarm antenna search (BSAS) algorithm withIterative Dichotomiser 3 (ID3) classification method was implied for ASDdetection and classification. The design of BSAS algorithm helps to determinethe parameter values of the ID3 classifier. The performance analysis of theASDC-OSAML model is performed using benchmark dataset. An extensivecomparison study highlighted the supremacy of the ASDC-OSAML modelover recent state of art approaches.

关 键 词：Autism spectral disorder machine learning owl search algorithm feature selection id3 classifier 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]