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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 |
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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 | |
Publication status | Published - 24 May 2021 |
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Springer Nature Switzerland AG (Publisher)
Jennifer Carter (Editor), Francisco Chiclana (Editor), Arjab Singh Khuman (Editor) & Tianhua Chen (Editor)
Oct 2019 → Oct 2020Activity: Publication peer-review and editorial work types › Editorial work