[HTML][HTML] Data mining in predicting liver patients using classification model
Purpose This study proposes to identify potential liver patients based on the results of a liver
function test performed during a health screening to search for signs of liver disease. It is …
function test performed during a health screening to search for signs of liver disease. It is …
Automated stratification of liver disease in ultrasound: an online accurate feature classification paradigm
Purpose Fatty liver disease (FLD) is one of the most common diseases in liver. Early
detection can improve the prognosis considerably. Using ultrasound for FLD detection is …
detection can improve the prognosis considerably. Using ultrasound for FLD detection is …
Artificial intelligence in precision medicine in hepatology
The advancement of investigation tools and electronic health records (EHR) enables a
paradigm shift from guideline‐specific therapy toward patient‐specific precision medicine …
paradigm shift from guideline‐specific therapy toward patient‐specific precision medicine …
[HTML][HTML] Enhanced preprocessing approach using ensemble machine learning algorithms for detecting liver disease
There has been a sharp increase in liver disease globally, and many people are dying
without even knowing that they have it. As a result of its limited symptoms, it is extremely …
without even knowing that they have it. As a result of its limited symptoms, it is extremely …
Enhancing Intelligence Diagnostic Accuracy Based on Machine Learning Disease Classification
According to recent research conducted by the World Health Organisation (WHO), there has
been a significant increase in the prevalence of liver and cardiac conditions. The rapid …
been a significant increase in the prevalence of liver and cardiac conditions. The rapid …
Machine learning based liver disease diagnosis: A systematic review
The computer-based approach is required for the non-invasive detection of chronic liver
diseases that are asymptomatic, progressive, and potentially fatal in nature. In this study, we …
diseases that are asymptomatic, progressive, and potentially fatal in nature. In this study, we …
Symtosis: A liver ultrasound tissue characterization and risk stratification in optimized deep learning paradigm
Abstract Background and Objective Fatty Liver Disease (FLD)-a disease caused by
deposition of fat in liver cells, is predecessor to terminal diseases such as liver cancer. The …
deposition of fat in liver cells, is predecessor to terminal diseases such as liver cancer. The …
Explainable AI for Enhanced Interpretation of Liver Cirrhosis Biomarkers
Liver cirrhosis is a terminal pathological result of chronic liver damage, illicit drugs,
hepatotoxicity, and non-alcoholic steatohepatitis. Assessment of liver cirrhosis via non …
hepatotoxicity, and non-alcoholic steatohepatitis. Assessment of liver cirrhosis via non …
An efficient classification of cirrhosis liver disease using hybrid convolutional neural network-capsule network
H Shaheen, K Ravikumar, NL Anantha… - … Signal Processing and …, 2023 - Elsevier
Liver cirrhosis is the diffuse and advanced phase of liver disease. Several morphological
methods are used for imaging modalities. But, these modalities are biased and lack in …
methods are used for imaging modalities. But, these modalities are biased and lack in …
The comparison of LightGBM and XGBoost coupling factor analysis and prediagnosis of acute liver failure
D Zhang, Y Gong - Ieee Access, 2020 - ieeexplore.ieee.org
This paper focuses on the comparison of dimensionality reduction effect between LightGBM
and XGBoost-FA. With respect to XGBoost, LightGBM can be built in the effect of …
and XGBoost-FA. With respect to XGBoost, LightGBM can be built in the effect of …