Social attention and autism detection in childhood using machine learning: A systematic review and meta-analysis
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Publisher
AIP Publishing
Link
http://aip.scitation.org/doi/pdf/10.1063/5.0152286
Reference24 articles.
1. Katuwal, G. J. (2017). Machine Learning Based Autism Detection Using Brain Imaging. Rochester Institute of Technology.
2. Altay, O., & Ulas, M. (2018, March). Prediction of the autism spectrum disorder diagnosis with linear discriminant analysis classifier and K-nearest neighbor in children. In 2018 6th International Symposium on Digital Forensic and Security (ISDFS) (pp. 1–4). IEEE.
3. Büyükoflaz, F. N., & Öztürk, A. (2018, May). Early autism diagnosis of children with machine learning algorithms. In 2018 26th Signal Processing and Communications Applications Conference (SIU) (pp. 1–4). IEEE.
4. Nicha C. Dvornek, Pamela Ventol, James S. Duncan, “Combining Phenotypic and Resting-State fMRI Data for Autism Classification with Recurrent Neural Networks”, IEEE 15th International Symposium on Biomedical Imaging, (2018) April, pp. 725–728.
5. Dingan Liao, Hu Lu, “Classify Autism and Control Based on Deep Learning and Community Structure on Resting-state fMRI”, IEEE Tenth International Conference on Advanced Computational Intelligence, (2018) March, pp. 289–294.
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