Application of artificial intelligence in gastroenterology

作     者：Young Joo Yang Chang Seok Bang 

作者机构：Department of Internal Medicine Hallym University College of Medicine 

出 版 物：《World Journal of Gastroenterology》 (世界胃肠病学杂志（英文版）)

年 卷 期：2019年第25卷第14期

页      面：1666-1683页

核心收录：

学科分类：10[医学] 

主　　题：Artificial intelligence Convolutional neural network Deep-learning Computer-assisted Gastroenterology Endoscopy 

摘      要：Artificial intelligence(AI) using deep-learning(DL) has emerged as a breakthrough computer technology. By the era of big data, the accumulation of an enormous number of digital images and medical records drove the need for the utilization of AI to efficiently deal with these data, which have become fundamental resources for a machine to learn by itself. Among several DL models, the convolutional neural network showed outstanding performance in image analysis. In the field of gastroenterology, physicians handle large amounts of clinical data and various kinds of image devices such as endoscopy and ultrasound. AI has been applied in gastroenterology in terms of diagnosis,prognosis, and image analysis. However, potential inherent selection bias cannot be excluded in the form of retrospective study. Because overfitting and spectrum bias(class imbalance) have the possibility of overestimating the accuracy,external validation using unused datasets for model development, collected in a way that minimizes the spectrum bias, is mandatory. For robust verification,prospective studies with adequate inclusion/exclusion criteria, which represent the target populations, are needed. DL has its own lack of *** interpretability is important in that it can provide safety measures, help to detect bias, and create social acceptance, further investigations should be performed.