AIMC Topic: Liver Cirrhosis
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Deep learning for noninvasive liver fibrosis classification: A systematic review.
Liver international : official journal of the International Association for the Study of the Liver
Jun 16, 2021
BACKGROUND AND AIMS: While biopsy is the gold standard for liver fibrosis staging, it poses significant risks. Noninvasive assessment of liver fibrosis is a growing field. Recently, deep learning (DL) technology has revolutionized medical image analy...
Liver fibrosis staging by deep learning: a visual-based explanation of diagnostic decisions of the model.
European radiology
May 20, 2021
OBJECTIVES: Deep learning has been proven to be able to stage liver fibrosis based on contrast-enhanced CT images. However, until now, the algorithm is used as a black box and lacks transparency. This study aimed to provide a visual-based explanation...
Detection of liver cirrhosis in standard T2-weighted MRI using deep transfer learning.
European radiology
May 11, 2021
OBJECTIVES: To investigate the diagnostic performance of deep transfer learning (DTL) to detect liver cirrhosis from clinical MRI.
Validation of a machine learning approach using FIB-4 and APRI scores assessed by the metavir scoring system: A cohort study.
Arab journal of gastroenterology : the official publication of the Pan-Arab Association of Gastroenterology
May 10, 2021
BACKGROUND AND STUDY AIM: The study aim was to improve and validate the accuracy of the fibrosis-4 (FIB-4) and aspartate aminotransferase-to-platelet ratio index (APRI) scores for use in a potential machine-learning (ML) method that accurately predic...
Feasibility of automatic detection of small hepatocellular carcinoma (≤2 cm) in cirrhotic liver based on pattern matching and deep learning.
Physics in medicine and biology
Apr 16, 2021
Early detection of hepatocellular carcinoma (HCC) is crucial for clinical management. Current studies have reported large HCC detections using automatic algorithms, but there is a lack of research on automatic detection of small HCCs (sHCCs). This st...
Microscope-Based Automated Quantification of Liver Fibrosis in Mice Using a Deep Learning Algorithm.
Toxicologic pathology
Mar 26, 2021
In preclinical studies that involve animal models for hepatic fibrosis, accurate quantification of the fibrosis is of utmost importance. The use of digital image analysis based on deep learning artificial intelligence (AI) algorithms can facilitate a...
High-dimensional hepatopath data analysis by machine learning for predicting HBV-related fibrosis.
Scientific reports
Mar 3, 2021
Chronic HBV infection, the main cause of liver cirrhosis and hepatocellular carcinoma, has become a global health concern. Machine learning algorithms are particularly adept at analyzing medical phenomenon by capturing complex and nonlinear relations...
A large-scale internal validation study of unsupervised virtual trichrome staining technologies on nonalcoholic steatohepatitis liver biopsies.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Dec 9, 2020
Non-alcoholic steatohepatitis (NASH) is a fatty liver disease characterized by accumulation of fat in hepatocytes with concurrent inflammation and is associated with morbidity, cirrhosis and liver failure. After extraction of a liver core biopsy, tis...
Adult
Male
Middle Aged
Severity of Illness Index
Adolescent
Humans
Child
Eosine Yellowish-(YS)
Neural Networks, Computer
Retrospective Studies
Staining and Labeling
Reproducibility of Results
Hematoxylin
Software
Clinical Decision-Making
Aged
Liver Cirrhosis
Decision Support Techniques
Methyl Green
Female
Aged, 80 and over
Young Adult
Coloring Agents
Liver
Microscopy
Predictive Value of Tests
Azo Compounds
Biopsy
Image Interpretation, Computer-Assisted
Non-alcoholic Fatty Liver Disease
Fully automated prediction of liver fibrosis using deep learning analysis of gadoxetic acid-enhanced MRI.
European radiology
Nov 17, 2020
OBJECTIVES: To (1) develop a fully automated deep learning (DL) algorithm based on gadoxetic acid-enhanced hepatobiliary phase (HBP) MRI and (2) compare the diagnostic performance of DL vs. MR elastography (MRE) for noninvasive staging of liver fibro...
Type IV Collagen 7S Is the Most Accurate Test For Identifying Advanced Fibrosis in NAFLD With Type 2 Diabetes.
Hepatology communications
Nov 16, 2020
This study aimed to examine whether the diagnostic accuracy of four noninvasive tests (NITs) for detecting advanced fibrosis in nonalcoholic fatty liver disease (NAFLD) is maintained or is inferior to with or without the presence of type 2 diabetes. ...
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