Machine learning predictive models for acute pancreatitis: A systematic review

Machine learning is gradually being widely used in predicting acute pancreatitis. No study has classified or summarised various prediction tasks for acute pancreatitis. The performance of models in different studies and the problems associated with model construction remain unclear. Machine learning-based models have great predictive performance, and outperform conventional statistical models and clinical scores in some prediction tasks for acute pancreatitis. The IJMEDI checklist is a new quality assessment tool, and scores can be attempted to be associated with it to evaluate the effects and reliability of machine learning-based models.