Gongcheng Kexue Yu Jishu/Advanced Engineering Science

Title : Machine Learning-Enhanced Neuroimaging for Precise Stroke Diagnosis: A Diagnostic Innovation
Dr. K. Nagi Reddy, Mrs. N. Vibhavari, Mrs. Hajira Sabuhi

Abstract :

metungtech.comStroke is one of the most prevalent causes of death and disability in the world, although it is preventable and treated. Improving clinical outcomes and lowering the burden of disease are significantly aided by early stroke detection and prompt treatments. Because machine learning techniques can be used to detect strokes, they have garnered a lot of attention in recent years. Finding trustworthy techniques, algorithms, and characteristics that support healthcare providers in making well-informed decisions on stroke prevention and treatment is the goal of this project. In order to accomplish this, we have created an early stroke detection system that uses brain CT scans in conjunction with the CNN algorithm to identify strokes at an extremely early stage. These CT image characteristics are incorporated into the CNN model. The diagnostic system's accuracy, precision, recall, F1 score, Receiver Operating Characteristic Cu

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