Using machine-learning algorithms to identify patients at high risk of upper gastrointestinal lesions for endoscopy.

Machine-learning algorithms can accurately and reliably predict the risk of UGI lesions based on readily available parameters. The predictive models have the potential to be used clinically for identifying patients with high risk of UGI lesions and stratifying patients for necessary endoscopic screening.