Improved liver disease prediction from clinical data through an evaluation of ensemble learning approaches.

The proposed model with gradient boosting bettered in most metrics compared with several recent similar works, suggesting its efficacy in predicting liver disease. It can be further applied to predict other diseases with the commonality of predicate indicators.