Artificial Intelligence Model for the Characterization of Biliary Strictures During Real-Time Digital Cholangioscopy: A Pilot Study

Abstract:

Aims We aimed to develop an artificial intelligence model for a real-time evaluation during digital cholangioscopy. Methods A single-center, pilot study. We collected 23 digital cholangioscopy videos for the training of the AI models using automated machine learning (AI Works, MD Consulting group, Ecuador). Three parameters were trained by two expert endoscopists. The AI classifies cholangioscopy findings as normal aspect, inflammatory aspect, and suggestive of malignancy. Biliary strictures’ final diagnosis was based on cholangioscopy visual impression, intraductal biopsy, and 6-months follow-up outcomes. Results A total of 1903 samples (1714 training and 189 testings) were used to train the AI. The automated learning process took 75 hours (2000 badges per parameter). The developed model reached a mean average precision (mAP) of 94.64%. The developed model had a total loss of 0.1988. The F1 …

Año de publicación:

2021

Keywords:

Fuente:

google