AIMC Topic: Hepatitis

Clear Filters Showing 1 to 9 of 9 articles

Enlightened prognosis: Hepatitis prediction with an explainable machine learning approach.

PloS one Apr 2, 2025
Hepatitis is a widespread inflammatory condition of the liver, presenting a formidable global health challenge. Accurate and timely detection of hepatitis is crucial for effective patient management, yet existing methods exhibit limitations that unde...
Logistic Models Support Vector Machine Decision Trees Machine Learning Prognosis Hepatitis Humans
View on PubMed DOI

Novel graph-based machine-learning technique for viral infectious diseases: application to influenza and hepatitis diseases.

Annals of medicine Jan 19, 2024
BACKGROUND: Most infectious diseases are caused by viruses, fungi, bacteria and parasites. Their ability to easily infect humans and trigger large-scale epidemics makes them a public health concern. Methods for early detection of these diseases have ...
Hepatitis Algorithms Humans Communicable Diseases Machine Learning Influenza, Human
View on PubMed DOI

Deep learning time series prediction models in surveillance data of hepatitis incidence in China.

PloS one Apr 13, 2022
BACKGROUND: Precise incidence prediction of Hepatitis infectious disease is critical for early prevention and better government strategic planning. In this paper, we presented different prediction models using deep learning methods based on the month...
Deep Learning China Incidence Time Factors Hepatitis Humans Forecasting
View on PubMed DOI

An Explainable Artificial Intelligence Framework for the Deterioration Risk Prediction of Hepatitis Patients.

Journal of medical systems Apr 13, 2021
In recent years, artificial intelligence-based computer aided diagnosis (CAD) system for the hepatitis has made great progress. Especially, the complex models such as deep learning achieve better performance than the simple ones due to the nonlinear ...
Humans Artificial Intelligence Machine Learning Hepatitis Diagnosis, Computer-Assisted Support Vector Machine
View on PubMed DOI

Correlation-Based Ensemble Feature Selection Using Bioinspired Algorithms and Classification Using Backpropagation Neural Network.

Computational and mathematical methods in medicine Sep 23, 2019
A framework for clinical diagnosis which uses bioinspired algorithms for feature selection and gradient descendant backpropagation neural network for classification has been designed and implemented. The clinical data are subjected to data preprocess...
Breast Neoplasms Diagnosis, Computer-Assisted Computational Biology Reproducibility of Results Sensitivity and Specificity Support Vector Machine Hepatitis Pattern Recognition, Automated Neural Networks, Computer Machine Learning Software Algorithms Computer Simulation Humans
View on PubMed DOI

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...
Alanine Transaminase Aspartate Aminotransferases Liver Function Tests Male Middle Aged Supervised Machine Learning Fatty Liver Disease Progression Case-Control Studies Non-alcoholic Fatty Liver Disease Humans Logistic Models Hepatitis Cohort Studies Risk Factors Biomarkers Liver Cirrhosis Health Status Aged Diabetes Mellitus, Type 2 Electronic Health Records Decision Trees Female
View on PubMed

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

Computational and mathematical methods in medicine Sep 24, 2017
Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Sev...
Humans Machine Learning Patient Selection Hepatitis Selection Bias Research Design Software Computer Simulation Algorithms Case-Control Studies
View on PubMed DOI

Application of a Combined Model with Autoregressive Integrated Moving Average (ARIMA) and Generalized Regression Neural Network (GRNN) in Forecasting Hepatitis Incidence in Heng County, China.

PloS one Jun 3, 2016
BACKGROUND: Hepatitis is a serious public health problem with increasing cases and property damage in Heng County. It is necessary to develop a model to predict the hepatitis epidemic that could be useful for preventing this disease.
Models, Theoretical Hepatitis China Incidence Humans Neural Networks, Computer Public Health
View on PubMed DOI

Classification of disease subtypes in medical spectroscopy for multi-category sample imbalances based on grouping and hierarchical learning.

Lasers in medical science May 19, 2025
In the medical domain, the challenges in sample acquisition and collection often result in imbalanced training sets for multi-class models, especially in disease subtype differentiation. We propose a novel method to address multi-class imbalance in s...
Machine Learning Spectrum Analysis, Raman Hepatitis Humans Neural Networks, Computer
View on PubMed DOI
Popular Topics
Recent Journals