Artificial intelligence in pancreaticobiliary endoscopy

Abstract

Artificial intelligence (AI) applications in health care have exponentially increased in recent years, and a few of these are related to pancreatobiliary disorders. AI‐based methods were applied to extract information, in prognostication, to guide clinical treatment decisions and in pancreatobiliary endoscopy to characterize lesions. AI applications in endoscopy are expected to reduce inter‐operator variability, improve the accuracy of diagnosis, and assist in therapeutic decision‐making in real time. AI‐based literature must however be interpreted with caution given the limited external validation. A multidisciplinary approach combining clinical and imaging or endoscopy data will better utilize AI‐based technologies to further improve patient care.

EASY‐APP: An artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis

“…The performance of the model was relatively low compared to the other works, with an AUC of the neural network at 0.769 and logistic regression at 0.607. Akshintala and Khashab 55 recently described the application of artificial intelligence to AP prediction in pancreaticobiliary endoscopy, presenting a simple AI‐based AP risk prediction calculator and decision‐making tool. All these previous results derived from relatively small cohorts 11 suggest the potential of machine learning models to improve upon handcrafted scores, an approach that we have exploited in our work.…”