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ASD-DiagNet: fMRI-Based ASD Detection by Nuzhat Tabassum is a document available to read on EtoBox.

The document presents ASD-DiagNet, a hybrid machine learning framework designed to classify Autism Spectrum Disorder (ASD) using fMRI data, aiming to improve diagnostic accuracy and reduce misdiagnosis. The approach combines an autoencoder for feature extraction with a single layer perceptron for classification, achieving up to 80% accuracy, which is significantly higher than existing methods. The proposed method also includes a data augmentation strategy to enhance training datasets, demonstrating efficien

Author

Nuzhat Tabassum

Language

EN