Application of artificial intelligence assisted diagnosis based on deep learning for early esophageal cancer
10.3760/cma.j.issn.1007-5232.2019.04.005
- VernacularTitle:基于深度学习的人工智能辅助诊断在食管早癌中的应用
- Author:
Shilun CAI
1
;
Ayimukedisi YALIKONG
;
Ran LI
;
Bo YAN
;
Liqing YAO
;
Pinghong ZHOU
;
Yunshi ZHONG
Author Information
1. 复旦大学附属中山医院内镜中心
- Keywords:
Endoscopy;
digestive system;
Early esophageal cancer;
Deep learning;
Computer-assisted diagnosis
- From:
Chinese Journal of Digestive Endoscopy
2019;36(4):246-250
- CountryChina
- Language:Chinese
-
Abstract:
Objective To improve the detection rate of early esophageal cancer during endoscopy by construction of artificial intelligence assistant diagnosis system. Methods A total of 2400 esophageal images were collected from Zhongshan Hospital of Fudan University from January 2016 to December 2017, including 1200 images of early esophageal cancer and 1200 images of normal esophageal mucosa. The lesions in pictures were marked with rectangular box by using computer program. Among them, 2000 pictures were divided into the training set and 400 pictures into the test set. An assistant diagnostic model of early esophageal cancer was established by back propagation algorithm in computer deep learning. The training model was tested and the sensitivity and specificity of the system at different cut-off points in the test set was calculated. Receiver operating characteristic ( ROC) curve was used to evaluate the performance of the diagnostic model. Results The area under ROC curve ( AUC) of the auxiliary diagnostic model was 0. 9961. The sensitivity and specificity were satisfactory. Conclusion The deep learning model constructed in this study has good specificity, sensitivity and AUC value in the diagnosis of early esophageal cancer, and can assist endoscopists in real-time diagnosis in clinical examination.
