Deep Learning Methods for Autism Spectrum Disorder Diagnosis Based on fMRI Images
Brain injuries are significant disorders affecting human life. Some of these damages can be completely eliminated by methods such as drug therapy. On the other hand, there is no known permanent treatment for damages caused by diseases such as Alzheimer, Autism spectrum disorder (ASD), Multiple scler...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Sakarya University
2021-04-01
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| Series: | Sakarya University Journal of Computer and Information Sciences |
| Subjects: | |
| Online Access: | https://dergipark.org.tr/tr/download/article-file/1575412 |
| _version_ | 1797351867851735040 |
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| author | Muhammed Ali Bayram İlyas Özer Feyzullah Temurtaş |
| author_facet | Muhammed Ali Bayram İlyas Özer Feyzullah Temurtaş |
| author_sort | Muhammed Ali Bayram |
| collection | DOAJ |
| description | Brain injuries are significant disorders affecting human life. Some of these damages can be completely eliminated by methods such as drug therapy. On the other hand, there is no known permanent treatment for damages caused by diseases such as Alzheimer, Autism spectrum disorder (ASD), Multiple sclerosis and Parkinson. Treatments aimed at slowing the progression of the disease are generally applied in these types of disorders. For this reason, essential to diagnose the disease at an early phase before behavioral disorders occur. In this study, a study is presented to detect ASD through resting-state functional magnetic resonance imaging rs-fMRI. However, fMRI data are highly complex data. Within the study's scope, ASD and healthy individuals were distinguished on 871 samples obtained from the ABIDE I data set. The long short-term memory network (LSTM), convolutional neural network (CNN) , and hybrid models are used together for the classification process. The results obtained are promising for the detection of ASD on fMRI. |
| first_indexed | 2024-03-08T13:06:45Z |
| format | Article |
| id | doaj.art-fc6c8cb4a36e49d8a48cdcf58f2ca8e7 |
| institution | Directory Open Access Journal |
| issn | 2636-8129 |
| language | English |
| last_indexed | 2024-03-08T13:06:45Z |
| publishDate | 2021-04-01 |
| publisher | Sakarya University |
| record_format | Article |
| series | Sakarya University Journal of Computer and Information Sciences |
| spelling | doaj.art-fc6c8cb4a36e49d8a48cdcf58f2ca8e72024-01-18T16:44:35ZengSakarya UniversitySakarya University Journal of Computer and Information Sciences2636-81292021-04-014114215510.35377/saucis.04.01.87973528Deep Learning Methods for Autism Spectrum Disorder Diagnosis Based on fMRI ImagesMuhammed Ali Bayram0İlyas Özer1Feyzullah Temurtaş2BANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİBANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİBANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİBrain injuries are significant disorders affecting human life. Some of these damages can be completely eliminated by methods such as drug therapy. On the other hand, there is no known permanent treatment for damages caused by diseases such as Alzheimer, Autism spectrum disorder (ASD), Multiple sclerosis and Parkinson. Treatments aimed at slowing the progression of the disease are generally applied in these types of disorders. For this reason, essential to diagnose the disease at an early phase before behavioral disorders occur. In this study, a study is presented to detect ASD through resting-state functional magnetic resonance imaging rs-fMRI. However, fMRI data are highly complex data. Within the study's scope, ASD and healthy individuals were distinguished on 871 samples obtained from the ABIDE I data set. The long short-term memory network (LSTM), convolutional neural network (CNN) , and hybrid models are used together for the classification process. The results obtained are promising for the detection of ASD on fMRI.https://dergipark.org.tr/tr/download/article-file/1575412deep learningrnnrs-fmriautism spectrum disorder |
| spellingShingle | Muhammed Ali Bayram İlyas Özer Feyzullah Temurtaş Deep Learning Methods for Autism Spectrum Disorder Diagnosis Based on fMRI Images Sakarya University Journal of Computer and Information Sciences deep learning rnn rs-fmri autism spectrum disorder |
| title | Deep Learning Methods for Autism Spectrum Disorder Diagnosis Based on fMRI Images |
| title_full | Deep Learning Methods for Autism Spectrum Disorder Diagnosis Based on fMRI Images |
| title_fullStr | Deep Learning Methods for Autism Spectrum Disorder Diagnosis Based on fMRI Images |
| title_full_unstemmed | Deep Learning Methods for Autism Spectrum Disorder Diagnosis Based on fMRI Images |
| title_short | Deep Learning Methods for Autism Spectrum Disorder Diagnosis Based on fMRI Images |
| title_sort | deep learning methods for autism spectrum disorder diagnosis based on fmri images |
| topic | deep learning rnn rs-fmri autism spectrum disorder |
| url | https://dergipark.org.tr/tr/download/article-file/1575412 |
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