Dyslexia Biomarker Detection Using Machine Learning

Dyslexia detection involves classification, pre-processing, feature extraction, and segmentation processes that are used to identify and classify the various Dyslexia images. A machine learning approach is being used in this proposed system which is used to detect and segment dyslexia in the brain region. The resulting outcome is analyzed for tumor detection in terms of evaluation parameters such as; sensitivity, specificity, and accuracy. Kaggle allows clients to discover and distribute informational indexes, investigate and construct models in an electronic information science environment, and other AI researchers and AI designs. By using programming tools like MATLAB, the existing and the proposed technique are implemented through simulation results, and the performance of the proposed technique is compared with the existing method to prove the effectiveness of the proposed algorithm.