AIMC Topic: Liver Cirrhosis

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Development, Validation, and Evaluation of a Simple Machine Learning Model to Predict Cirrhosis Mortality.

JAMA network open Nov 2, 2020
IMPORTANCE: Machine-learning algorithms offer better predictive accuracy than traditional prognostic models but are too complex and opaque for clinical use.
Humans Machine Learning Middle Aged Time Factors ROC Curve Logistic Models Liver Cirrhosis Databases, Factual Retrospective Studies Female Aged Male
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An index based on deep learning-measured spleen volume on CT for the assessment of high-risk varix in B-viral compensated cirrhosis.

European radiology Oct 30, 2020
OBJECTIVES: Deep learning enables an automated liver and spleen volume measurements on CT. The purpose of this study was to develop an index combining liver and spleen volumes and clinical factors for detecting high-risk varices in B-viral compensate...
Spleen Herpesvirus 1, Cercopithecine Varicose Veins Deep Learning Liver Cirrhosis Predictive Value of Tests Esophageal and Gastric Varices Humans Retrospective Studies Tomography, X-Ray Computed
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Assessment of a Deep Learning Model to Predict Hepatocellular Carcinoma in Patients With Hepatitis C Cirrhosis.

JAMA network open Sep 1, 2020
IMPORTANCE: Deep learning, a family of machine learning models that use artificial neural networks, has achieved great success at predicting outcomes in nonmedical domains.
Humans Neural Networks, Computer Prognosis Liver Cirrhosis Area Under Curve Hepatitis C, Chronic Sustained Virologic Response Veterans Health Services Risk Assessment Chronic Disease Indicators Deep Learning Electronic Health Records Incidence Female Liver Neoplasms Male Carcinoma, Hepatocellular Middle Aged
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Automated quantification and architectural pattern detection of hepatic fibrosis in NAFLD.

Annals of diagnostic pathology Apr 12, 2020
Accurate detection and quantification of hepatic fibrosis remain essential for assessing the severity of non-alcoholic fatty liver disease (NAFLD) and its response to therapy in clinical practice and research studies. Our aim was to develop an integr...
Non-alcoholic Fatty Liver Disease Fibrosis Azo Compounds Collagen Automation Liver Biopsy Pathologists Supervised Machine Learning Eosine Yellowish-(YS) Methyl Green Portal Vein Practice Patterns, Physicians' Clinical Trials as Topic Organ Dysfunction Scores Humans Artificial Intelligence Severity of Illness Index Image Processing, Computer-Assisted Liver Cirrhosis
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Diagnostic accuracy of texture analysis and machine learning for quantification of liver fibrosis in MRI: correlation with MR elastography and histopathology.

European radiology Apr 8, 2020
OBJECTIVES: To compare the diagnostic accuracy of texture analysis (TA)-derived parameters combined with machine learning (ML) of non-contrast-enhanced T1w and T2w fat-saturated (fs) images with MR elastography (MRE) for liver fibrosis quantification...
Magnetic Resonance Imaging Liver Biopsy Elasticity Imaging Techniques Female Male Middle Aged ROC Curve Liver Cirrhosis Humans Machine Learning Prospective Studies
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Assessment of liver fibrosis severity using computed tomography-based liver and spleen volumetric indices in patients with chronic liver disease.

European radiology Feb 13, 2020
OBJECTIVES: To evaluate whether the liver and spleen volumetric indices, measured on portal venous phase CT images, could be used to assess liver fibrosis severity in chronic liver disease.
Spleen Severity of Illness Index Case-Control Studies Deep Learning ROC Curve Tomography, X-Ray Computed Liver Cirrhosis Liver Humans Female Chronic Disease Retrospective Studies Adult Organ Size Male Liver Diseases Middle Aged
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Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis.

European radiology Jan 21, 2020
OBJECTIVES: To propose a transfer learning (TL) radiomics model that efficiently combines the information from gray scale and elastogram ultrasound images for accurate liver fibrosis grading.
Hepatitis B, Chronic Humans Data Accuracy Neural Networks, Computer Elasticity Imaging Techniques Female ROC Curve Machine Learning Aged Liver Cirrhosis Adult Algorithms Liver Male Biomarkers Area Under Curve Middle Aged Retrospective Studies
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Multiclass Classification of Hepatic Anomalies with Dielectric Properties: From Phantom Materials to Rat Hepatic Tissues.

Sensors (Basel, Switzerland) Jan 18, 2020
Open-ended coaxial probes can be used as tissue characterization devices. However, the technique suffers from a high error rate. To improve this technology, there is a need to decrease the measurement error which is reported to be more than 30% for a...
Female Animals Logistic Models Rats, Wistar Rats Liver Cirrhosis Liver Equipment Design Electrophysiology Phantoms, Imaging Electrophysiological Phenomena Machine Learning Algorithms
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Detecting liver fibrosis using a machine learning-based approach to the quantification of the heart-induced deformation in tagged MR images.

NMR in biomedicine Nov 15, 2019
Liver disease causes millions of deaths per year worldwide, and approximately half of these cases are due to cirrhosis, which is an advanced stage of liver fibrosis that can be accompanied by liver failure and portal hypertension. Early detection of ...
Heart Male Systole Humans Middle Aged Machine Learning Time Factors Female Liver Cirrhosis Adult Magnetic Resonance Imaging
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Non-invasive diagnosis of non-alcoholic steatohepatitis and fibrosis with the use of omics and supervised learning: A proof of concept study.

Metabolism: clinical and experimental Nov 9, 2019
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 25-30% of the general population and is characterized by the presence of non-alcoholic fatty liver (NAFL) that can progress to non-alcoholic steatohepatitis (NASH), liver fibrosis and cirr...
Non-alcoholic Fatty Liver Disease Fatty Acids Humans Proof of Concept Study Male Female Middle Aged Metabolomics Case-Control Studies Lipids Fatty Liver Polysaccharides Liver Cirrhosis Supervised Machine Learning
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