Revolutionizing Neurological Diagnostics
The Role of Deep Learning
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Neurological disorders pose a significant global health burden, affecting millions of individuals and imposing considerable challenges on healthcare systems. Early and accurate diagnosis is crucial for effective management and treatment. In recent years, deep learning methods have emerged as powerful tools for medical image analysis, offering promising avenues for automated detection and diagnosis of neurological disorders. This abstract provides an overview of the current state of research in this field, highlighting key methodologies, challenges, and future directions. Neurological disorders...
Neurological disorders pose a significant global health burden, affecting millions of individuals and imposing considerable challenges on healthcare systems. Early and accurate diagnosis is crucial for effective management and treatment. In recent years, deep learning methods have emerged as powerful tools for medical image analysis, offering promising avenues for automated detection and diagnosis of neurological disorders. This abstract provides an overview of the current state of research in this field, highlighting key methodologies, challenges, and future directions. Neurological disorders encompass a broad range of conditions affecting the nervous system, including the brain, spinal cord, and peripheral nerves. Traditional diagnostic approaches often rely on clinical assessments, which may be subjective and timeconsuming. The advent of deep learning techniques has revolutionized medical image analysis, enabling the development of automated systems that can assist in the early and accurate detection of neurological disorders. Epilepsy is a neurological disorder characterized as the recurrence of two or more unprovoked seizures. The common and significant tool for aiding in the identification of epilepsy is electroencephalography (EEG).
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