Endoscopic prediction of submucosal invasion in Barrett’s cancer with the use of artificial intelligence: a pilot study
Alanna Ebigbo, Robert Mendel, Tobias Rückert, Laurin Schuster, Andreas Probst, Johannes Manzeneder, Friederike Prinz, Matthias Mende, Ingo Steinbrück, Siegbert Faiss, David Rauber, Luis A de Souza Jr, João P Papa, Pierre H Deprez, Tsuneo Oyama, Akiko Takahashi, Stefan Seewald, Prateek Sharma, Michael F Byrne, Christoph Palm, Helmut Messmann
The accurate differentiation between T1a and T1b Barrett's-related cancer has both therapeutic and prognostic implications but is challenging even for experienced physicians. We trained an artificial intelligence (AI) system on the basis of deep artificial neural networks (deep learning) to differentiate between T1a and T1b Barrett's cancer on white-light images.
