Neurointel: A Cognitive Neural Disorder Prediction System Using Machine Learning Algorithms and Sequential CNN

Abstract

The rise in neurological disorders within modern society emphasizes the critical need for accurate diagnosis and immediate treatment. Traditional diagnostic methods mostly depend on specialized Neurologists and primarily utilize MRI scans and related neuroimaging techniques to evaluate the neurological health of patients. With today’s growing need for diagnosing neural disorders, we need more prominent automated diagnostic tools to enhance medical practices. In this system, we propose a novel approach to diagnosing neurological disorders such as Alzheimer's Disease, Brain tumor and Brain stroke using Sequential Convolutional Neural Networks (CNNs) and machine learning algorithms. Our system utilizes the CNN at most of its capabilities in analyzing neuroimaging data and extracting key features that indicate neurological disorders. Through rigorous training and validation processes, the system achieves notable accuracy in the identification and classification of neurological disorders based on neuroscan findings. This enhances healthcare delivery by improving patient outcomes in the field of neurology.