AIMC Topic: Fatty Liver

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Liver Attenuation Assessment in Reduced Radiation Chest Computed Tomography.

Journal of computer assisted tomography Jun 3, 2022
OBJECTIVE: This study aimed to evaluate the reliability of liver and spleen Hounsfield units (HU) measurements in reduced radiation computed tomography (RRCT) of the chest within the sub-millisievert range.
Tomography, X-Ray Computed Artificial Intelligence Reproducibility of Results Fatty Liver Prospective Studies Retrospective Studies Humans
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Cascaded Deep Learning Neural Network for Automated Liver Steatosis Diagnosis Using Ultrasound Images.

Sensors (Basel, Switzerland) Aug 5, 2021
Diagnosing liver steatosis is an essential precaution for detecting hepatocirrhosis and liver cancer in the early stages. However, automatic diagnosis of liver steatosis from ultrasound (US) images remains challenging due to poor visual quality from ...
Image Processing, Computer-Assisted Fatty Liver Deep Learning Ultrasonography Humans Neural Networks, Computer
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Machine Learning Algorithms for Predicting Fatty Liver Disease.

Annals of nutrition & metabolism Apr 13, 2021
BACKGROUND: Fatty liver disease (FLD) has become a rampant condition. It is associated with a high rate of morbidity and mortality in a population. The condition is commonly referred as FLD. Early prediction of FLD would allow patients to take necess...
Machine Learning Algorithms Female Humans Logistic Models Middle Aged Clinical Decision Rules Adult Predictive Value of Tests Risk Assessment Area Under Curve Fatty Liver Male
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Transfer learning with pre-trained deep convolutional neural networks for the automatic assessment of liver steatosis in ultrasound images.

Medical ultrasonography Dec 29, 2020
AIM: In this paper we proposed different architectures of convolutional neural network (CNN) to classify fatty liver disease in images using only pixels and diagnosis labels as input. We trained and validated our models using a dataset of 629 images ...
Humans Middle Aged Deep Learning Ultrasonography Fatty Liver
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Use of a convolutional neural network and quantitative ultrasound for diagnosis of fatty liver.

Ultrasound in medicine & biology Dec 25, 2020
Quantitative ultrasound (QUS) was used to classify rabbits that were induced to have liver disease by placing them on a fatty diet for a defined duration and/or periodically injecting them with CCl. The ground truth of the liver state was based on li...
Dietary Fats Male Ultrasonography Fatty Liver Neural Networks, Computer Liver Machine Learning Rabbits Animals Non-alcoholic Fatty Liver Disease
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Combining Data with Predictions for Modeling Hepatic Steatosis by Using Stratified Bagging and Conformal Prediction.

Chemical research in toxicology Dec 21, 2020
Hepatic steatosis (fatty liver) is a severe liver disease induced by the excessive accumulation of fatty acids in hepatocytes. In this study, we developed reliable models for predicting hepatic steatosis on the basis of an data set of 1041 compound...
Fatty Liver Models, Molecular Molecular Conformation Hydrocarbons, Aromatic Hydrocarbons, Acyclic Machine Learning Databases, Factual Computer Simulation Humans
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Parameter estimation of the homodyned K distribution based on an artificial neural network for ultrasound tissue characterization.

Ultrasonics Dec 1, 2020
The homodyned K (HK) distribution allows a general description of ultrasound backscatter envelope statistics with specific physical meanings. In this study, we proposed a new artificial neural network (ANN) based parameter estimation method of the HK...
Computer Simulation Ultrasonography Image Processing, Computer-Assisted Humans Neural Networks, Computer Fatty Liver Tissue Donors
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AI finally provides augmented intelligence to liver surgeons.

EBioMedicine Oct 20, 2020
Liver Transplantation Primary Graft Dysfunction Fatty Liver Liver Biopsy Surgeons Humans Deep Learning Artificial Intelligence
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Editorial Comment on "Liver Steatosis Categorization on Contrast-Enhanced CT Using a Fully Automated Deep Learning Volumetric Segmentation Tool: Evaluation in 1204 Healthy Adults Using Unenhanced CT as a Reference Standard".

AJR. American journal of roentgenology Sep 30, 2020
Reference Standards Adult Humans Deep Learning Tomography, X-Ray Computed Fatty Liver
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Deep learning quantification of percent steatosis in donor liver biopsy frozen sections.

EBioMedicine Sep 24, 2020
BACKGROUND: Pathologist evaluation of donor liver biopsies provides information for accepting or discarding potential donor livers. Due to the urgent nature of the decision process, this is regularly performed using frozen sectioning at the time of b...
Fatty Liver Living Donors Biopsy Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Frozen Sections Liver Transplantation Severity of Illness Index Immunohistochemistry Molecular Sequence Annotation
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