Implementation Learning Vector Quantization Using Neural Network for Classification of Ear, Nose and Throat Disease

Abstract This study aims to use data from 57 patients at Rantauprapat Hospital train a Neural Network using quantization learning vector method for the categorization of ear, nose, and throat disorders. The input factors were fever, tiredness, nausea, breathing pain, sore throat, hearing loss, allergies, chills sweating, thick transparent mucus. studied ear canal infections, pharyngitis neck, sinusitis. findings revealed that ten neurons with an objective value 0.01 in rate range - 0.05 resulted categorizing snoring, disorders, including layer. MATLAB program is utilized this approach, average accuracy 67 per cent mean square error 0.2.