PREDICTION OF NEUROLOGICAL DISEASE USING MACHINE LEARNING

In the modern era, neurological diseases are a growing concern. Finding neurological disease in its early stages is a challenging task for a doctor. However, accurate disease diagnosis at an early stage is crucial because treatments are more likely to enhance patients’ quality of life at that point. We suggest a statistical approach using the most prevalent symptoms of neurological diseases, which are gait, tremors, and micrographic, since there is no established test to identify the symptoms. In order to find the classification algorithm that provides the highest accuracy in diagnosing the patients, this involves analyzing the correlation between both the symptoms and classifying the obtained data using various classification algorithms. Greater medical care and higher standards of care may result from earlier detection.