Classification of Nonalcoholic Fatty Liver Grades using Pre-Trained Convolutional Neural Networks and a Random Forest Classifier on B-Mode Ultrasound Images
Abstract:Background: Nonalcoholic Fatty Liver Disease (NAFLD) as a prevalent condition can significantly have health implications. Early detection and accurate grading of NAFLD are essential for effective management and treatment of the disease.Objective: The current study aimed to develop an advanced hybrid machinelearning model to classify NAFLD grades using ultrasound images.
Material and Methods:In this analytical study, ultrasound images were obtained from 55 highly obese individuals, who had undergone bariatric s… Show more
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