Enhancing Liver Cirrhosis Diagnosis Using Machine Learning With Explainable AI and Cross-Validated Hyperparameter Tuning Techniques
This research sought to design and assess a novel and non-invasive proposed model by utilizing the XGBoost classifier with Explainable Artificial Intelligence (XAI) for diagnosing liver cirrhosis and results have shown superiority for the proposed method compared with various machine learning models.