Influence of expert-dependent variability over the performance of noninvasive fibrosis assessment in patients with chronic hepatitis C by means of texture analysis

DOI10.1155/2012/346713zbMath1233.92040OpenAlexW2052472328WikidataQ35645808 ScholiaQ35645808MaRDI QIDQ764145

Cristian Vicas, Sergiu Nedevschi, Mihai Socaciu, Monica Lupsor, Radu Badea

Publication date: 13 March 2012

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2012/346713

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Biomedical imaging and signal processing (92C55) Medical applications (general) (92C50) Analysis of variance and covariance (ANOVA) (62J10) Computational methods for problems pertaining to biology (92-08)

Uses Software

• LIBSVM

Cites Work

• Unnamed Item
• Unnamed Item
• Texture segmentation based on estimated MRF parameters
• Logistic model trees
• The elements of statistical learning. Data mining, inference, and prediction

This page was built for publication: Influence of expert-dependent variability over the performance of noninvasive fibrosis assessment in patients with chronic hepatitis C by means of texture analysis