AIMC Topic: Fatty Liver

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AI finally provides augmented intelligence to liver surgeons.

EBioMedicine Oct 20, 2020
Fatty Liver Liver Biopsy Liver Transplantation Primary Graft Dysfunction Humans Artificial Intelligence Surgeons Deep Learning
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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
Tomography, X-Ray Computed Adult Deep Learning Fatty Liver Reference Standards Humans
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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...
Biopsy Liver Transplantation Immunohistochemistry Humans Molecular Sequence Annotation Neural Networks, Computer Frozen Sections Algorithms Deep Learning Severity of Illness Index Image Processing, Computer-Assisted Fatty Liver Living Donors
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Using machine learning algorithms to review computed tomography scans and assess risk for cardiovascular disease: Retrospective analysis from the National Lung Screening Trial (NLST).

PloS one Aug 3, 2020
BACKGROUND: The National Lung Screening Trial (NLST) demonstrated that annual screening with low dose CT in high-risk population was associated with reduction in lung cancer mortality. Nonetheless, the leading cause of mortality in the study was from...
Emphysema Cigarette Smoking Coronary Vessels Clinical Trials, Phase III as Topic National Cancer Institute (U.S.) Lung Lung Neoplasms Fatty Liver United States Mass Screening Early Detection of Cancer Liver Randomized Controlled Trials as Topic Radiographic Image Interpretation, Computer-Assisted Male Cardiovascular Diseases Middle Aged Risk Assessment Humans Retrospective Studies Machine Learning Tomography, X-Ray Computed Female Risk Factors
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Deep-learning-based accurate hepatic steatosis quantification for histological assessment of liver biopsies.

Laboratory investigation; a journal of technical methods and pathology Jul 13, 2020
Hepatic steatosis droplet quantification with histology biopsies has high clinical significance for risk stratification and management of patients with fatty liver diseases and in the decision to use donor livers for transplantation. However, patholo...
Humans Software Biopsy Radiographic Image Interpretation, Computer-Assisted Image Interpretation, Computer-Assisted Algorithms Deep Learning Fatty Liver Liver
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Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.

PLoS medicine Jun 19, 2020
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible dama...
Humans Machine Learning Prospective Studies Female Fatty Liver Models, Statistical Diabetes Complications Reproducibility of Results Male Middle Aged Risk Assessment
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Ultrasonic liver steatosis quantification by a learning-based acoustic model from a novel shear wave sequence.

Biomedical engineering online Dec 21, 2019
BACKGROUND: An efficient and accurate approach to quantify the steatosis extent of liver is important for clinical practice. For the purpose, we propose a specific designed ultrasound shear wave sequence to estimate ultrasonic and shear wave physical...
Image Processing, Computer-Assisted Young Adult Fatty Liver Humans Adult Models, Biological Shear Strength Machine Learning Male Acoustics Triglycerides Female Middle Aged Phantoms, Imaging Aged Ultrasonography
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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...
Fatty Liver Liver Cirrhosis Metabolomics Lipids Polysaccharides Supervised Machine Learning Non-alcoholic Fatty Liver Disease Fatty Acids Proof of Concept Study Female Male Middle Aged Case-Control Studies Humans
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Prediction of fatty liver disease using machine learning algorithms.

Computer methods and programs in biomedicine Dec 29, 2018
BACKGROUND AND OBJECTIVE: Fatty liver disease (FLD) is a common clinical complication; it is associated with high morbidity and mortality. However, an early prediction of FLD patients provides an opportunity to make an appropriate strategy for preven...
Humans Neural Networks, Computer Fatty Liver Machine Learning Taiwan Early Diagnosis Aged Algorithms Adult Forecasting Male Electronic Health Records Middle Aged Female ROC Curve
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Application of Machine Learning Methods to Predict Non-Alcoholic Steatohepatitis (NASH) in Non-Alcoholic Fatty Liver (NAFL) Patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease worldwide. NAFLD patients have excessive liver fat (steatosis), without other liver diseases and without excessive alcohol consumption. NAFLD consists of a spectr...
Aspartate Aminotransferases Disease Progression Liver Function Tests Case-Control Studies Risk Factors Fatty Liver Supervised Machine Learning Cohort Studies Humans Aged Non-alcoholic Fatty Liver Disease Logistic Models Diabetes Mellitus, Type 2 Biomarkers Male Hepatitis Liver Cirrhosis Electronic Health Records Middle Aged Alanine Transaminase Female Health Status Decision Trees
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