Development of an Explainable Computational Framework for the Early Detection of Neurological Conditions
This research investigates deep learning techniques and advanced time-series analysis within Computer Science to process electroencephalography (EEG) data. The primary objective is to build robust, high-performance computational models while emphasizing interpretability, transparency, and clinical relevance for the early detection of neurodegenerative diseases.
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