DEVELOPMENT AND VALIDATION OF AN ONLINE DYNAMIC NOMOGRAM BASED ON THE ATHEROGENIC INDEX OF PLASMA TO SCREEN NONALCOHOLIC FATTY LIVER DISEASE

Development and validation of an online dynamic nomogram based on the atherogenic index of plasma to screen nonalcoholic fatty liver disease

Abstract Background Nonalcoholic fatty liver disease (NAFLD), a common liver disease worldwide, can be reversed early in life pc850q with lifestyle and medical interventions.This study aimed to develop a noninvasive tool to screen NAFLD accurately.Methods Risk factors for NAFLD were identified using multivariate logistic regression analysis, and an

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Unsupervised Video Shot Detection Using Clustering Ensemble with a Color Global Scale-Invariant Feature Transform Descriptor

Scale-invariant feature transform (SIFT) transforms a grayscale image into scale-invariant coordinates of local features that are invariant to image scale, rotation, and changing viewpoints.Because of its scale-invariant properties, SIFT has been successfully used for object recognition and content-based image retrieval.The biggest drawback of SIFT

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