Autism Spectrum Disorder Classification Using a Self-organising Fuzzy Classifier

Jonathan  Stirling; Tianhua Chen; Marios Adamou

doi:10.1007/978-3-030-66474-9_6

Autism Spectrum Disorder Classification Using a Self-organising Fuzzy Classifier

Jonathan Stirling, Tianhua Chen, Marios Adamou

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that covers a range of symptoms such as impaired social skills and repetitive behaviours. The diagnosis of ASD in clinics is typically lengthy and cost-ineffective. Recent advances in machine learning could facilitate more efficient and effective detection of ASD. However, fuzzy systems, as a significant soft computing technique, have been sporadically applied in the diagnosis of ASD. This chapter therefore examines the use of a recently proposed Self-Organising Fuzzy Classifier with application to the “Autism Screening Adult” data retrieved from a mobile application.

Original language	English
Title of host publication	Fuzzy Logic
Subtitle of host publication	Recent Applications and Developments
Editors	Jenny Carter, Francisco Chiclana, Arjab Singh Khuman, Tianhua Chen
Place of Publication	Cham
Publisher	Springer Nature Switzerland AG
Chapter	6
Pages	83-94
Number of pages	12
Edition	1
ISBN (Electronic)	9783030664749
ISBN (Print)	9783030664732, 9783030664763
DOIs	https://doi.org/10.1007/978-3-030-66474-9_6
Publication status	Published - 24 May 2021

Access to Document

10.1007/978-3-030-66474-9_6Licence: Unspecified

Cite this

@inbook{8aabb210232c4ebcba4824a5c81589dd,

title = "Autism Spectrum Disorder Classification Using a Self-organising Fuzzy Classifier",

abstract = "Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that covers a range of symptoms such as impaired social skills and repetitive behaviours. The diagnosis of ASD in clinics is typically lengthy and cost-ineffective. Recent advances in machine learning could facilitate more efficient and effective detection of ASD. However, fuzzy systems, as a significant soft computing technique, have been sporadically applied in the diagnosis of ASD. This chapter therefore examines the use of a recently proposed Self-Organising Fuzzy Classifier with application to the “Autism Screening Adult” data retrieved from a mobile application.",

keywords = "Autism Spectrum Disorder, Classification, Self-Organising Fuzzy Classifier, ASD, Clinical decision support, Fuzzy systems, SOF",

author = "Jonathan Stirling and Tianhua Chen and Marios Adamou",

year = "2021",

month = may,

day = "24",

doi = "10.1007/978-3-030-66474-9_6",

language = "English",

isbn = "9783030664732",

pages = "83--94",

editor = "Jenny Carter and Chiclana, {Francisco } and {Singh Khuman}, Arjab and Tianhua Chen",

booktitle = "Fuzzy Logic",

publisher = "Springer Nature Switzerland AG",

address = "Switzerland",

edition = "1",

}

Autism Spectrum Disorder Classification Using a Self-organising Fuzzy Classifier. / Stirling, Jonathan ; Chen, Tianhua; Adamou, Marios.

Fuzzy Logic: Recent Applications and Developments. ed. / Jenny Carter; Francisco Chiclana; Arjab Singh Khuman; Tianhua Chen. 1. ed. Cham : Springer Nature Switzerland AG, 2021. p. 83-94.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Autism Spectrum Disorder Classification Using a Self-organising Fuzzy Classifier

AU - Stirling, Jonathan

AU - Chen, Tianhua

AU - Adamou, Marios

PY - 2021/5/24

Y1 - 2021/5/24

N2 - Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that covers a range of symptoms such as impaired social skills and repetitive behaviours. The diagnosis of ASD in clinics is typically lengthy and cost-ineffective. Recent advances in machine learning could facilitate more efficient and effective detection of ASD. However, fuzzy systems, as a significant soft computing technique, have been sporadically applied in the diagnosis of ASD. This chapter therefore examines the use of a recently proposed Self-Organising Fuzzy Classifier with application to the “Autism Screening Adult” data retrieved from a mobile application.

AB - Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that covers a range of symptoms such as impaired social skills and repetitive behaviours. The diagnosis of ASD in clinics is typically lengthy and cost-ineffective. Recent advances in machine learning could facilitate more efficient and effective detection of ASD. However, fuzzy systems, as a significant soft computing technique, have been sporadically applied in the diagnosis of ASD. This chapter therefore examines the use of a recently proposed Self-Organising Fuzzy Classifier with application to the “Autism Screening Adult” data retrieved from a mobile application.

KW - Autism Spectrum Disorder

KW - Classification

KW - Self-Organising Fuzzy Classifier

KW - ASD

KW - Clinical decision support

KW - Fuzzy systems

KW - SOF

UR - https://www.springer.com/gb/book/9783030664732

U2 - 10.1007/978-3-030-66474-9_6

DO - 10.1007/978-3-030-66474-9_6

M3 - Chapter

SN - 9783030664732

SN - 9783030664763

SP - 83

EP - 94

BT - Fuzzy Logic

A2 - Carter, Jenny

A2 - Chiclana, Francisco

A2 - Singh Khuman, Arjab

A2 - Chen, Tianhua

PB - Springer Nature Switzerland AG

CY - Cham

ER -

Autism Spectrum Disorder Classification Using a Self-organising Fuzzy Classifier

Abstract

Access to Document

Other files and links

Fingerprint

Springer Nature Switzerland AG (Publisher)

Cite this

Autism Spectrum Disorder Classification Using a Self-organising Fuzzy Classifier

Abstract

Access to Document

Other files and links

Fingerprint

Activities

Springer Nature Switzerland AG (Publisher)

Cite this