[HTML][HTML] A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation
Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …
belonging to one class is lower than the other. Ensemble learning combines multiple models …
A Machine Learning‐Based Framework for Accurate and Early Diagnosis of Liver Diseases: A Comprehensive Study on Feature Selection, Data Imbalance, and …
The liver is the largest organ of the human body with more than 500 vital functions. In recent
decades, a large number of liver patients have been reported with diseases such as …
decades, a large number of liver patients have been reported with diseases such as …
Liver disease classification using histogram-based gradient boosting classification tree with feature selection algorithm
P Theerthagiri - Biomedical Signal Processing and Control, 2025 - Elsevier
Healthcare is the key for everyone to run daily life, and health diagnosing techniques should
be accessible easily. Indeed, the early identification of liver disease will be supportive for …
be accessible easily. Indeed, the early identification of liver disease will be supportive for …
Polynomial-SHAP analysis of liver disease markers for capturing of complex feature interactions in machine learning models
Liver disease diagnosis is pivotal for effective patient management, and machine learning
techniques have shown promise in this domain. In this study, we investigate the impact of …
techniques have shown promise in this domain. In this study, we investigate the impact of …
A unified foot and mouth disease dataset for Uganda: evaluating machine learning predictive performance degradation under varying distributions
In Uganda, the absence of a unified dataset for constructing machine learning models to
predict Foot and Mouth Disease outbreaks hinders preparedness. Although machine …
predict Foot and Mouth Disease outbreaks hinders preparedness. Although machine …
[HTML][HTML] A comparative analysis of boosting algorithms for chronic liver disease prediction
Chronic liver disease (CLD) is a major health concern for millions of people all over the
globe. Early prediction and identification are critical for taking appropriate action at the …
globe. Early prediction and identification are critical for taking appropriate action at the …
An efficient liver disease prediction using mask-regional convolutional neural network and pelican optimization algorithm
Various prediction approaches regarding liver diseases have been developed. Still, they are
expensive and more complex. This work aims to design an effective method for identifying …
expensive and more complex. This work aims to design an effective method for identifying …
RG-SVM: Recursive gaussian support vector machine based feature selection algorithm for liver disease classification
P Theerthagiri… - Multimedia Tools and …, 2024 - Springer
Health is an essential concern for everyone, so it is necessary to facilitate medical services
that are easily accessible to everyone. The primary goal of this work is to predict liver …
that are easily accessible to everyone. The primary goal of this work is to predict liver …
Design of a Collaborative Knowledge Framework for Personalised Attention Deficit Hyperactivity Disorder (ADHD) Treatments
P Chatpreecha, S Usanavasin - Children, 2023 - mdpi.com
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder. From the
data collected by the Ministry of Public Health, Thailand, it has been reported that more than …
data collected by the Ministry of Public Health, Thailand, it has been reported that more than …
Liver disease detection and prediction using SVM techniques
Because of the high prevalence and mortality rate of liver disease, early diagnosis is
essential. Machine learning techniques can be introduced in the diagnosis and treatment of …
essential. Machine learning techniques can be introduced in the diagnosis and treatment of …