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Published in: Cognitive Neurodynamics 6/2023

12-11-2022 | Research Article

Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy regression

Authors: Afshin Shoeibi, Navid Ghassemi, Marjane Khodatars, Parisa Moridian, Abbas Khosravi, Assef Zare, Juan M. Gorriz, Amir Hossein Chale-Chale, Ali Khadem, U. Rajendra Acharya

Published in: Cognitive Neurodynamics | Issue 6/2023

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Abstract

Nowadays, many people worldwide suffer from brain disorders, and their health is in danger. So far, numerous methods have been proposed for the diagnosis of Schizophrenia (SZ) and attention deficit hyperactivity disorder (ADHD), among which functional magnetic resonance imaging (fMRI) modalities are known as a popular method among physicians. This paper presents an SZ and ADHD intelligent detection method of resting-state fMRI (rs-fMRI) modality using a new deep learning method. The University of California Los Angeles dataset, which contains the rs-fMRI modalities of SZ and ADHD patients, has been used for experiments. The FMRIB software library toolbox first performed preprocessing on rs-fMRI data. Then, a convolutional Autoencoder model with the proposed number of layers is used to extract features from rs-fMRI data. In the classification step, a new fuzzy method called interval type-2 fuzzy regression (IT2FR) is introduced and then optimized by genetic algorithm, particle swarm optimization, and gray wolf optimization (GWO) techniques. Also, the results of IT2FR methods are compared with multilayer perceptron, k-nearest neighbors, support vector machine, random forest, and decision tree, and adaptive neuro-fuzzy inference system methods. The experiment results show that the IT2FR method with the GWO optimization algorithm has achieved satisfactory results compared to other classifier methods. Finally, the proposed classification technique was able to provide 72.71% accuracy.

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Metadata
Title
Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy regression
Authors
Afshin Shoeibi
Navid Ghassemi
Marjane Khodatars
Parisa Moridian
Abbas Khosravi
Assef Zare
Juan M. Gorriz
Amir Hossein Chale-Chale
Ali Khadem
U. Rajendra Acharya
Publication date
12-11-2022
Publisher
Springer Netherlands
Published in
Cognitive Neurodynamics / Issue 6/2023
Print ISSN: 1871-4080
Electronic ISSN: 1871-4099
DOI
https://doi.org/10.1007/s11571-022-09897-w

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