Optimizing HCV Disease Prediction in Egypt: The hyOPTGB Framework
The paper focuses on the hepatitis C virus (HCV) infection in Egypt, which has one of the
highest rates of HCV in the world. The high prevalence is linked to several factors, including …
highest rates of HCV in the world. The high prevalence is linked to several factors, including …
hyOPTGB: An Efficient OPTUNA Hyperparameter Optimization Framework for Hepatitis C Virus (HCV) Disease Prediction in Egypt
AM Elshewey - 2023 - researchsquare.com
The paper focuses on Hepatitis C Virus (HCV) infection in Egypt, which has one of the
highest rates of HCV in the world. The high prevalence is linked to several factors, including …
highest rates of HCV in the world. The high prevalence is linked to several factors, including …
Hepatitis C virus (HCV) prediction by machine learning techniques
Hepatitis C being as a prevalent disease in the world especially in countries like Egypt. It is
estimated that 3-4 million new cases every year, indicating as a public health problem and …
estimated that 3-4 million new cases every year, indicating as a public health problem and …
Performance comparison of machine learning approaches on hepatitis C prediction employing data mining techniques
A Alizargar, YL Chang, TH Tan - Bioengineering, 2023 - mdpi.com
Hepatitis C is a liver infection caused by the hepatitis C virus (HCV). Due to the late onset of
symptoms, early diagnosis is difficult in this disease. Efficient prediction can save patients …
symptoms, early diagnosis is difficult in this disease. Efficient prediction can save patients …
Hepatitis C Virus prediction based on machine learning framework: a real-world case study in Egypt
H Mamdouh Farghaly, MY Shams… - … and Information Systems, 2023 - Springer
Prediction and classification of diseases are essential in medical science, as it attempts to
immune the spread of the disease and discover the infected regions from the early stages …
immune the spread of the disease and discover the infected regions from the early stages …
An optimized XGBoost approach for predicting progression of hepatitis c using hyperparameter tuning and feature interaction constraint
KR Singh, R Gupta, RK Kadian… - 2022 2nd Asian …, 2022 - ieeexplore.ieee.org
Hepatitis C is a prominent viral infection affecting the liver, which has an estimated 58 million
active cases throughout the world, with 1.5 million new infections adding to this tally every …
active cases throughout the world, with 1.5 million new infections adding to this tally every …
Application of Machine Learning Algorithms in Predicting Hepatitis C
Y Wang, B Yin, Q Zhu - Proceedings of the 2023 4th International …, 2023 - dl.acm.org
Hepatitis C, caused by the hepatitis C virus (HCV) infection, is a disease that can progress
from initial asymptomatic stages to chronic infection if left untreated, potentially leading to …
from initial asymptomatic stages to chronic infection if left untreated, potentially leading to …
Applying data mining techniques to classify patients with suspected hepatitis C virus infection
Background Hepatitis C virus (HCV) has a high prevalence worldwide, and the progression
of the disease can cause irreversible damage to severe liver damage or even death …
of the disease can cause irreversible damage to severe liver damage or even death …
Hybrid model for precise hepatitis-C classification using improved random forest and SVM method
Abstract Hepatitis C Virus (HCV) is a viral infection that causes liver inflammation. Annually,
approximately 3.4 million cases of HCV are reported worldwide. A diagnosis of HCV in …
approximately 3.4 million cases of HCV are reported worldwide. A diagnosis of HCV in …
Hepatitis C Prediction Using Feature Selection by Machine Learning Technique
J Majumder, S Ghosh, A Khang, T Debnath… - Medical Robotics and …, 2024 - igi-global.com
This study suggests a prediction framework for the Hepatitis C virus that is based on
machine learning techniques. The authors made use of a dataset available on Kaggle. In …
machine learning techniques. The authors made use of a dataset available on Kaggle. In …