Development of a visual attention based decision support system for autism spectrum disorder screening

被引：15

作者：

Ozdemir, Selda ^{[1
]}

Akin-Bulbul, Isik ^{[2
]}

Kok, Ibrahim ^{[3
]}

Ozdemir, Suat ^{[4
]}

机构：

[1] Hacettepe Univ, Hacettepe Educ Fac, Dept Special Educ, Ankara, Turkey

[2] Gazi Univ, Gazi Educ Fac, Special Educ Dept Teknikokullar, Ankara, Turkey

[3] Pamukkale Univ, Engn Fac, Comp Engn Dept, Denizli, Turkey

[4] Hacettepe Univ, Engn Fac, Comp Engn Dept, Ankara, Turkey

来源：

INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY | 2022年 / 173卷

关键词：

Autism spectrum disorders; Eye tracking; Visual attention; Screening; Machine learning; Biomarker; SOCIAL ATTENTION; CIRCUMSCRIBED INTERESTS; EARLY IDENTIFICATION; EYE-TRACKING; CHILDREN; TODDLERS; PATTERNS; ADULTS; BRAIN; IMPAIRMENT;

D O I：

10.1016/j.ijpsycho.2022.01.004

中图分类号：

B84 [心理学];

学科分类号：

04 ; 0402 ;

摘要：

Visual attention of young children with autism spectrum disorder (ASD) has been well documented in the literature for the past 20 years. In this study, we developed a Decision Support System (DSS) that uses machine learning (ML) techniques to identify young children with ASD from typically developing (TD) children. Study participants included 26 to 36 months old young children with ASD (n = 61) and TD children (n = 72). The results showed that the proposed DSS achieved up to 87.5% success rate in the early assessment of ASD in young children. Findings suggested that visual attention is a unique, promising biomarker for early assessment of ASD. Study results were discussed, and suggestions for future research were provided.

引用

页码：69 / 81

页数：13

共 77 条

[1] Machine learning approach for early detection of autism by combining questionnaire and home video screening [J].

Abbas, Halim ;

Garberson, Ford ;

Glover, Eric ;

Wall, Dennis P. .

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2018, 25 (08) :1000-1007

[2] Improving the Naive Bayes Classifier via a Quick Variable Selection Method Using Maximum of Entropy [J].

Abellan, Joaquin ;

Castellano, Javier G. .

ENTROPY, 2017, 19 (06)

[3] An Expanded View of Joint Attention: Skill, Engagement, and Language in Typical Development and Autism [J].

Adamson, Lauren B. ;

Bakeman, Roger ;

Suma, Katharine ;

Robins, Diana L. .

CHILD DEVELOPMENT, 2019, 90 (01) :e1-e18

[4] Building predictive models for MERS-CoV infections using data mining techniques [J].

Al-Turaiki, Isra ;

Alshahrani, Mona ;

Almutairi, Tahani .

JOURNAL OF INFECTION AND PUBLIC HEALTH, 2016, 9 (06) :744-748

[5] Bayley scales of infant and toddler development, third edition. [J].

Albers, Craig A. ;

Grieve, Adam J. .

JOURNAL OF PSYCHOEDUCATIONAL ASSESSMENT, 2007, 25 (02) :180-190

[6]

[Anonymous], 2018, Morbidity and Mortality Weekly Report. Surveillance Summaries (Washington, V70, P1, DOI [DOI 10.15585/MMWR.SS7011A1, 10.15585/mmwr.ss7011a1external icon, DOI 10.15585/MMWR.SS7202A1]

[7]

APA, 1980, Diagnostic and statistical manual of mental disorders

[8] Disentangling the initiation from the response in joint attention: an eye-tracking study in toddlers with autism spectrum disorders [J].

Billeci, L. ;

Narzisi, A. ;

Campatelli, G. ;

Crifaci, G. ;

Calderoni, S. ;

Gagliano, A. ;

Calzone, C. ;

Colombi, C. ;

Pioggia, G. ;

Muratori, F. .

TRANSLATIONAL PSYCHIATRY, 2016, 6 :e808-e808

[9]

Bishop L.S., 2010, AUTISM SPECTRUM DISO, P23

[10] How can clinicians detect and treat autism early? Methodological trends of technology use in research [J].

Bolte, S. ;

Bartl-Pokorny, K. D. ;

Jonsson, U. ;

Berggren, S. ;

Zhang, D. ;

Kostrzewa, E. ;

Falck-Ytter, T. ;

Einspieler, C. ;

Pokorny, F. B. ;

Jones, E. J. H. ;

Roeyers, H. ;

Charman, T. ;

Marschik, P. B. .

ACTA PAEDIATRICA, 2016, 105 (02) :137-144

← 1 2 3 4 5 6 7 8 →