Towards physician's experience: Development of machine learning model for the diagnosis of autism spectrum disorders based on complex <scp>T</scp> ‐spherical fuzzy‐weighted zero‐inconsistency method-Reference-Cited by-同舟云学术

Towards physician's experience: Development of machine learning model for the diagnosis of autism spectrum disorders based on complex T ‐spherical fuzzy‐weighted zero‐inconsistency method

Published:2022-12-05 Issue:2 Volume:39 Page:225-257
ISSN:0824-7935
Container-title:Computational Intelligence
language:en
Short-container-title:Computational Intelligence

Author:

Albahri Ahmed S.¹,Zaidan Aws A.²,AlSattar Hassan A.³^ORCID,A. Hamid Rula¹,Albahri Osamah S.⁴,Qahtan Sarah⁵,Alamoodi Abdulla H.⁶

Affiliation:

1. Informatics Institute for Postgraduate Studies (IIPS) Iraqi Commission for Computers and Informatics (ICCI) Baghdad Iraq

2. Faculty of Engineering and IT The British University in Dubai Dubai United Arab Emirates

3. Department of Business Administration, College of Administrative Sciences The University of Mashreq Baghdad Iraq

4. Computer Techniques Engineering Department Mazaya University College Nasiriyah Iraq

5. Department of Computer Center, College of Health and Medical Techniques Middle Technical University Baghdad Iraq

6. Department of Computing, Faculty of Arts, Computing and Creative Industry Universiti Pendidikan Sultan Idris Tanjung Malim Malaysia

Publisher

Wiley

Subject

Artificial Intelligence,Computational Mathematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/coin.12562

Reference167 articles.

1. Global Prevalence of Autism and Other Pervasive Developmental Disorders

2. A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG

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