AIMC Topic: Liver Cirrhosis

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Ultrasound and SWE-based transfer learning for predicting fibrotic NASH.

Scientific reports
The aim of this study was to develop a combined deep-learning model utilizing liver ultrasound, liver elastography images, and clinical features to predict and diagnose fibrotic non-alcoholic steatohepatitis (NASH). A rat model of liver steatosis and...

Identifying SUMOylation-related genes in liver fibrosis with bioinformatics and experimental models for diagnostic insights.

Scientific reports
Liver fibrosis (LF) is a medical disorder caused by prolonged chronic liver injury, which, if left untreated, can progress to cirrhosis or liver cancer, posing significant risks to patient health. In recent years, the increase in liver diseases, incl...

Use of machine learning for early prediction of short-term mortality in veterans with metabolic dysfunction-associated steatotic liver disease.

PloS one
BACKGROUND: Metabolic dysfunction associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide and affects >25% in the United States population. We hypothesized that clinical features present in electronic health r...

Rapid Liver Fibrosis Evaluation Using the UNet-ResNet50-32 × 4d Model in Magnetic Resonance Elastography: Retrospective Study.

JMIR medical informatics
BACKGROUND: Liver fibrosis is a pathological outcome of chronic liver injury and a hallmark of multiple chronic liver diseases. Magnetic resonance elastography (MRE) provides a non-invasive modality for evaluating the severity of liver fibrosis.

Comparison of artificial neural network-predicted PPG and HVPG with measured PPG in decompensated cirrhosis patients.

Scientific reports
Portal hypertension (PHT) is pivotal in managing decompensated cirrhosis. In clinical practice, hepatic venous collaterals are frequently present, often leading to failure or reduced accuracy of hepatic venous pressure gradient (HVPG) measurements, t...

Paired snRNA-seq and scRNA-seq analysis of MASLD patients to identify early-stage markers for disease progression.

Hepatology communications
BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide. Progression from simple metabolic dysfunction-associated steatotic liver (MASL) without necro-inflammation to...

Neutrophil extracellular trapping network-associated biomarkers in liver fibrosis: machine learning and experimental validation.

Journal of translational medicine
BACKGROUND: The diagnostic and therapeutic potential of neutrophil extracellular traps (NETs) in liver fibrosis (LF) has not been fully explored. We aim to screen and verify NETs-related liver fibrosis biomarkers through machine learning.

Predicting Unplanned Readmission Risk in Patients With Cirrhosis: Complication-Aware Dynamic Classifier Selection Approach.

JMIR medical informatics
BACKGROUND: Cirrhosis is a leading cause of noncancer deaths in gastrointestinal diseases, resulting in high hospitalization and readmission rates. Early identification of high-risk patients is vital for proactive interventions and improving health c...

Machine learning-based prediction model for 28-day mortality in acute kidney injury patients with liver cirrhosis: A MIMIC-IV database analysis.

PloS one
BACKGROUND: Acute kidney injury (AKI) in patients with liver cirrhosis represents a significant clinical challenge with high mortality rates. This study aimed to develop and validate a machine learning-based prediction model for 28-day mortality in A...