Machine learning-based detection of electrosurgical device-induced bleeding in laparoscopic videos of diaphragmatic hernia repair

The presented work on device-induced bleeding detection is a step toward quantifying the effect of electrosurgery use. We showed a machine learning-based methodology that accurately identifies video fragments of device activations without bleeding but struggles to identify bleeding precisely. Future work should focus on developing device-induced bleeding detection in a larger, more diverse dataset.