Advancing Multimodal Intelligence in Colonoscopy

Advancing Multimodal Intelligence in Colonoscopy

A new study maps the rapidly evolving field of intelligent colonoscopy. It argues that the next leap will come not from isolated-task modeling alone, but from generalized multimodal systems that can perceive, describe, locate, and discuss findings in clinically useful language. To move the field forward, the researchers broadly reviewed 63 datasets and 137 deep-learning models spanning classification, detection, segmentation, and vision-language