International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | An Explainable Machine Learning Framework for Liver Disease Prediction Using Dual Statistical Feature Optimization and Ensemble Learning |
|---|---|
| ABSTRACT | Liver disease continues to be a major global health concern due to its silent progression and delayed diagnosis. This study proposes an efficient and interpretable machine learning framework for early liver disease prediction by integrating advanced preprocessing, Dual Statistical Feature Optimization (DSFO), and ensemble learning. Missing values are handled using iterative imputation techniques, while class imbalance is addressed using SMOTE to ensure balanced data distribution. The proposed DSFO method combines Chi-Square dependency analysis and ANOVA-based variance evaluation to identify the most significant clinical features. Unlike conventional stacking approaches, the model employs a simplified ensemble strategy using LightGBM and Extra Trees Classifier combined through soft voting, improving generalization while reducing model complexity. The framework achieved an accuracy of 97.96% and ROC-AUC of 0.9894, demonstrating strong predictive capability. To enhance interpretability, SHAP is used to provide insights into feature contributions. Results reveal that biochemical attributes such as bilirubin and liver enzyme levels play a dominant role in prediction. The proposed system offers a reliable and transparent solution suitable for real-world clinical applications. |
| AUTHOR | POLEMREDDY VENKATA ALEKHYA, DR. DEEPAK NEDUNURI M. Tech Scholar, Department of CSE, Sir C R Reddy College of Engineering, Eluru, India Professor, Department of CSE, Sir C R Reddy College of Engineering, Eluru, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404144 |
| pdf/144_An Explainable Machine Learning Framework for Liver Disease Prediction Using Dual Statistical Feature Optimization and Ensemble Learning.pdf | |
| KEYWORDS | |
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