GastroNet-5M: A Multicenter Dataset for Developing Foundation Models in Gastrointestinal Endoscopy

This study presents GastroNet-5M, a dataset of ∼5 million endoscopic images. Pretraining endoscopic deep learning systems with GastroNet-5M improves diagnostic accuracy, reduces the need for scarce application-specific endoscopic imagery and annotations, and increases their robustness to the inevitable data heterogeneity in clinical practice. This may significantly accelerate development and implementation of endoscopic AI systems. GastroNet-5M is publicly available for scientific use.