Journal of Engineering and Engineering Technology - JEET |A THEORETIC UTILITY OF AUGMENTING GENERALIZED REGRESSION NEURAL NETWORK

Paper Details

Title :A THEORETIC UTILITY OF AUGMENTING GENERALIZED REGRESSION NEURAL NETWORK
Author(s) : Ojie D. V. (1), Ogala Onyarin Justin (2) and Okpako Abugor Ejaita (3)
DOI: https://doi.org/10.51459/futajeet.2024.01.02.19
Abstract:

The inclusion of computing devices in the diagnostic phase in medical care has received a disturbing publicity owing to its inherent benefits: practicality, reproducibility, efficiency, and immunity to disturbance variables unique to humans (fatigue, stress, diminished attention). Technology does not replace human professionals in this area of medical support; instead, it aims to aid them by developing systems that can pick up or create appropriate data. In medicine, diagnosis is defined as "the detection of a disease or condition based on its outward signs and symptoms" or "the investigation of the underlying physiological, biochemical cause." Hepatitis B, which includes chronic liver disease, is quite widespread worldwide and can harm hepatocytes. Cirrhosis can range in severity from healthy carriers to decompensated cirrhosis. We have developed an intelligent framework for identifying hepatitis B viral illness in this research. Hepatitis is a dangerous disease that requires expensive treatment and severe side effects. The generalized regression neural network is a suitable and promising approach to detection and prediction of severity of Hepatitis B in patients.

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