Detecting early gastric cancer: Comparison between the diagnostic ability of convolutional neural networks and endoscopists

Y Ikenoyama, T Hirasawa, M Ishioka… - Digestive …, 2021 - Wiley Online Library
Objectives Detecting early gastric cancer is difficult, and it may even be overlooked by
experienced endoscopists. Recently, artificial intelligence based on deep learning through …

Development and validation of a real-time artificial intelligence-assisted system for detecting early gastric cancer: A multicentre retrospective diagnostic study

D Tang, L Wang, T Ling, Y Lv, M Ni, Q Zhan, Y Fu… - …, 2020 - thelancet.com
Background We aimed to develop and validate a real-time deep convolutional neural
networks (DCNNs) system for detecting early gastric cancer (EGC). Methods All 45,240 …

[HTML][HTML] A deep neural network improves endoscopic detection of early gastric cancer without blind spots

L Wu, W Zhou, X Wan, J Zhang, L Shen, S Hu… - …, 2019 - thieme-connect.com
Background Gastric cancer is the third most lethal malignancy worldwide. A novel deep
convolution neural network (DCNN) to perform visual tasks has been recently developed …

Application of convolutional neural network in the diagnosis of the invasion depth of gastric cancer based on conventional endoscopy

Y Zhu, QC Wang, MD Xu, Z Zhang, J Cheng… - Gastrointestinal …, 2019 - Elsevier
Background and Aims According to guidelines, endoscopic resection should only be
performed for patients whose early gastric cancer invasion depth is within the mucosa or …

Deep learning system compared with expert endoscopists in predicting early gastric cancer and its invasion depth and differentiation status (with videos)

L Wu, J Wang, X He, Y Zhu, X Jiang, Y Chen… - Gastrointestinal …, 2022 - Elsevier
Background and Aims We aimed to develop and validate a deep learning–based system
that covers various aspects of early gastric cancer (EGC) diagnosis, including detecting …

Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images

T Hirasawa, K Aoyama, T Tanimoto, S Ishihara… - Gastric Cancer, 2018 - Springer
Background Image recognition using artificial intelligence with deep learning through
convolutional neural networks (CNNs) has dramatically improved and been increasingly …

Automated classification of gastric neoplasms in endoscopic images using a convolutional neural network

BJ Cho, CS Bang, SW Park, YJ Yang, SI Seo… - …, 2019 - thieme-connect.com
Background Visual inspection, lesion detection, and differentiation between malignant and
benign features are key aspects of an endoscopist's role. The use of machine learning for …

Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study

H Hu, L Gong, D Dong, L Zhu, M Wang, J He… - Gastrointestinal …, 2021 - Elsevier
Background and Aims Narrow-band imaging with magnifying endoscopy (ME-NBI) has
shown advantages in the diagnosis of early gastric cancer (EGC). However, proficiency in …

Real-time artificial intelligence for detection of upper gastrointestinal cancer by endoscopy: a multicentre, case-control, diagnostic study

H Luo, G Xu, C Li, L He, L Luo, Z Wang, B Jing… - The Lancet …, 2019 - thelancet.com
Background Upper gastrointestinal cancers (including oesophageal cancer and gastric
cancer) are the most common cancers worldwide. Artificial intelligence platforms using deep …

Automatic detection of early gastric cancer in endoscopic images using a transferring convolutional neural network

Y Sakai, S Takemoto, K Hori… - 2018 40th Annual …, 2018 - ieeexplore.ieee.org
Endoscopic image diagnosis assisted by machine learning is useful for reducing
misdetection and interobserver variability. Although many results have been reported, few …