AIMC Topic: Liver Cirrhosis

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Integrative Analysis of Proteomic, Glycomic, and Metabolomic Data for Biomarker Discovery.

IEEE journal of biomedical and health informatics
Studies associating changes in the levels of multiple biomolecules including proteins, glycans, glycoproteins, and metabolites with the onset of cancer have been widely investigated to identify clinically relevant diagnostic biomarkers. Advances in l...

Machine Learning Classification of Cirrhotic Patients with and without Minimal Hepatic Encephalopathy Based on Regional Homogeneity of Intrinsic Brain Activity.

PloS one
Machine learning-based approaches play an important role in examining functional magnetic resonance imaging (fMRI) data in a multivariate manner and extracting features predictive of group membership. This study was performed to assess the potential ...

The impact of paracentesis flow rate in patients with liver cirrhosis on the development of paracentesis induced circulatory dysfunction.

Clinical and molecular hepatology
BACKGROUND/AIMS: Ascites is a dreadful complication of liver cirrhosis associated with short survival. Large volume paracentesis (LVP) is used to treat tense or refractory ascites. Paracentesis induced circulatory dysfunction (PICD) develops if no pl...

Serum tests, liver stiffness and artificial neural networks for diagnosing cirrhosis and portal hypertension.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: The diagnostic performance of biochemical scores and artificial neural network models for portal hypertension and cirrhosis is not well established.

Analyses of a cirrhotic patient's evolution using self organizing mapping and Child-Pugh scoring.

Journal of medical systems
Due to the importance of cirrhosis evolution, this study examined cirrhotic patients using Self Organizing Mapping (SOM) based on the Child-Pugh scoring method. Because Colored Doppler Ultrasound (CDU) has too many parameters, scoring can be a very d...

Enhancing HF-DL Model Validation for Liver Fibrosis Staging Through Sample Optimisation and Technical Integration.

Liver international : official journal of the International Association for the Study of the Liver
We read with great interest the article by Zhang et al. The study demonstrates that the deep learning model based on high-frequency ultrasound images significantly outperforms the low-frequency ultrasound model, FIB-4, APRI, and shear wave elastograp...

Digital Pathology Quantification of the Continuum of Cirrhosis Severity in Human Liver Biopsies.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: Liver biopsy is the gold standard for assessing fibrosis in cirrhotic livers, yet cirrhosis is spatially heterogeneous and continuously remodels. This study evaluates a novel phenotypic digital pathology platform for continuous f...

A Deep Learning Model Based on High-Frequency Ultrasound Images for Classification of Different Stages of Liver Fibrosis.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: To develop a deep learning model based on high-frequency ultrasound images to classify different stages of liver fibrosis in chronic hepatitis B patients.