Application of artificial intelligence in pancreaticobiliary diseases

Therapeutic Advances in Gastrointestinal Endoscopy

Review

Rupinder Mann¹  Abhilash Perisetti²  Zainab Gandhi³  Zhongheng Zhang⁴  Shreyas Saligram⁵  Neil Sharma⁶  Sumant Inamdar⁷  Benjamin Tharian⁷  Hemant Goyal⁸ 

[1] Academic Hospitalist, Saint Agnes Medical Center, Fresno, CA, USA;Department of Gastroenterology and Hepatology, The University of Arkansas for Medical Sciences, Little Rock, AR, USA;Department of Medicine, Geisinger Community Medical Center, Scranton, PA, USA;Department of emergency medicine, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China;Division of Advanced Endoscopy, Gastroenterology, Hepatology, and Nutrition, Department of Medicine, University of Texas Health, San Antonio, TX, USA;Division of Interventional Oncology & Surgical Endoscopy (IOSE), Parkview Cancer Institute, Fort Wayne, IN, USA;University of Arkansas for Medical Sciences, Little Rock, AR, USA;null;

关键词: artificial intelligence;    choledocholithiasis;    computer-aided diagnosis;    endoscopic ultrasound;    pancreatic cancer;   

DOI  :  10.1177/2631774521993059

 received in 2020-08-02, accepted in 2021-01-11,  发布年份 2021

来源: Sage Journals

【 摘 要 】

The role of artificial intelligence and its applications has been increasing at a rapid pace in the field of gastroenterology. The application of artificial intelligence in gastroenterology ranges from colon cancer screening and characterization of dysplastic and neoplastic polyps to the endoscopic ultrasonographic evaluation of pancreatic diseases. Artificial intelligence has been found to be useful in the evaluation and enhancement of the quality measure for endoscopic retrograde cholangiopancreatography. Similarly, artificial intelligence techniques like artificial neural networks and faster region-based convolution network are showing promising results in early and accurate diagnosis of pancreatic cancer and its differentiation from chronic pancreatitis. Other artificial intelligence techniques like radiomics-based computer-aided diagnosis systems could help to differentiate between various types of cystic pancreatic lesions. Artificial intelligence and computer-aided systems also showing promising results in the diagnosis of cholangiocarcinoma and the prediction of choledocholithiasis. In this review, we discuss the role of artificial intelligence in establishing diagnosis, prognosis, predicting response to treatment, and guiding therapeutics in the pancreaticobiliary system.

【 授权许可】

CC BY-NC   
© The Author(s) 2021

【 图 表 】

Figure 7.