Advancements in automated diagnosis of autism spectrum disorder through deep learning and resting-state functional mri biomarkers: a systematic review
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11571-024-10176-z.pdf
Reference43 articles.
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3. Al-Hiyali MI, Yahya N, Faye I, et al (2021) Classification of bold fmri signals using wavelet transform and transfer learning for detection of autism spectrum disorder. In 2020 IEEE-EMBS conference on biomedical engineering and sciences (IECBES), IEEE, 94–98
4. Almuqhim F, Saeed F (2021) Asd-saenet: a sparse autoencoder, and deep-neural network model for detecting autism spectrum disorder (asd) using fmri data. Front Comput Neurosci 15:654315
5. Alsaade FW, Alzahrani MS et al (2022) Classification and detection of autism spectrum disorder based on deep learning algorithms. Comput Intell Neurosci 2022(1):8709145
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