AIMC Topic: Liver Function Tests

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A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein.

Scientific reports Jul 1, 2025
Metabolic Syndrome (MetS) comprises a clustering of conditions that significantly increase the risk of heart disease, stroke, and diabetes. Timely detection and intervention are crucial in preventing severe health outcomes. In this study, we implemen...
Machine Learning Algorithms Biomarkers Female Aged Humans Neural Networks, Computer C-Reactive Protein Alanine Transaminase Aspartate Aminotransferases Bilirubin Liver Function Tests Adult Male Middle Aged Support Vector Machine Metabolic Syndrome
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A pilot study for the prediction of liver function related scores using breath biomarkers and machine learning.

Scientific reports Feb 7, 2022
Volatile organic compounds (VOCs) present in exhaled breath can help in analysing biochemical processes in the human body. Liver diseases can be traced using VOCs as biomarkers for physiological and pathophysiological conditions. In this work, we pro...
Butadienes Hemiterpenes Machine Learning Liver Diseases Biomarkers Liver Function Tests Pilot Projects Limonene Predictive Value of Tests Breath Tests Sulfides Exhalation Volatile Organic Compounds
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Intrahepatic cholestasis of pregnancy: machine-learning algorithm to predict elevated bile acid based on clinical and laboratory data.

Archives of gynecology and obstetrics Feb 19, 2021
PURPOSE: Applying machine-learning models to clinical and laboratory features of women with intrahepatic cholestasis of pregnancy (ICP) and creating algorithm to identify these patients without bile acid measurements.
Humans Machine Learning Algorithms Retrospective Studies Pregnancy Bile Acids and Salts Cholestasis, Intrahepatic Pregnancy Complications Female Liver Function Tests Infant, Newborn Adult Pregnancy Outcome
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Application of machine learning in the diagnosis of gastric cancer based on noninvasive characteristics.

PloS one Dec 31, 2020
BACKGROUND: The diagnosis of gastric cancer mainly relies on endoscopy, which is invasive and costly. The aim of this study is to develop a predictive model for the diagnosis of gastric cancer based on noninvasive characteristics.
Humans Machine Learning Female Aged Stomach Neoplasms Sensitivity and Specificity Biomarkers, Tumor Male Middle Aged Liver Function Tests CA-125 Antigen Kidney Function Tests Predictive Value of Tests CA-19-9 Antigen Blood Cell Count
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The Challenges of Implementing Artificial Intelligence into Surgical Practice.

World journal of surgery Oct 13, 2020
BACKGROUND: Artificial intelligence is touted as the future of medicine. Classical algorithms for the detection of common bile duct stones (CBD) have had poor clinical uptake due to low accuracy. This study explores the challenges of developing and i...
Adult Male Middle Aged Predictive Value of Tests Acute Disease Retrospective Studies Female Aged Aged, 80 and over Biliary Tract Diseases Cholangiopancreatography, Endoscopic Retrograde Bilirubin Liver Function Tests Choledocholithiasis Humans Artificial Intelligence Machine Learning Computer Simulation
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Neural Network-Based Study about Correlation Model between TCM Constitution and Physical Examination Indexes Based on 950 Physical Examinees.

Journal of healthcare engineering Sep 1, 2020
PURPOSE: To establish the correlation model between Traditional Chinese Medicine (TCM) constitution and physical examination indexes by backpropagation neural network (BPNN) technology. A new method for the identification of TCM constitution in clini...
Software Blood Chemical Analysis Liver Function Tests Algorithms Urinalysis Reproducibility of Results Models, Statistical Humans Physical Examination Computer Systems Lipids Neural Networks, Computer Medicine, Chinese Traditional Programming Languages Artificial Intelligence Data Collection Pattern Recognition, Automated
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Results of Green Indocyanine in the Use of the R1T1 Robot as Aid in the Pre-operative Process of Hepatic Organ Transplant: Experiment in Wistar Rats.

Transplantation proceedings May 24, 2020
Since the beginning of the history of transplants, numerous difficulties have been faced in the effective implementation of this therapeutic practice, especially with regard to the transplantation of solid organs and their teaching and training, toge...
Liver Robotics Liver Transplantation Indocyanine Green Liver Function Tests Transplants Humans Animals Male Rats, Wistar Rats
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Liver disease screening based on densely connected deep neural networks.

Neural networks : the official journal of the International Neural Network Society Nov 11, 2019
Liver disease is an important public health problem. Liver Function Tests (LFT) is the most achievable test for liver disease diagnosis. Most liver diseases are manifested as abnormal LFT. Liver disease screening by LFT data is helpful for computer a...
Liver Function Tests Humans Deep Learning Liver Diseases
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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...
Liver Function Tests Non-alcoholic Fatty Liver Disease Case-Control Studies Risk Factors Logistic Models Humans Cohort Studies Hepatitis Aged Biomarkers Liver Cirrhosis Alanine Transaminase Male Diabetes Mellitus, Type 2 Electronic Health Records Health Status Aspartate Aminotransferases Middle Aged Fatty Liver Decision Trees Female Disease Progression Supervised Machine Learning
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Complex analyses on clinical information systems using restricted natural language querying to resolve time-event dependencies.

Journal of biomedical informatics Apr 9, 2018
PURPOSE: This paper reports on a generic framework to provide clinicians with the ability to conduct complex analyses on elaborate research topics using cascaded queries to resolve internal time-event dependencies in the research questions, as an ext...
Acetaminophen Out-of-Hospital Cardiac Arrest Humans Medical Informatics Body Temperature Software Medical Records Systems, Computerized Algorithms Liver Function Tests Language Natural Language Processing Data Science Internet User-Computer Interface Fever Time Factors Programming Languages Brain Injuries, Traumatic Data Collection Liver
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