Comparison of performances of artificial intelligence versus expert endoscopists for real-time assisted diagnosis of esophageal squamous cell carcinoma (with video)
Hiromu Fukuda(Osaka International Cancer Institute), Tomohiro Tada(American Society for Gastrointestinal Endoscopy), Tsutomu Nishida(Toyonaka Municipal Hospital), Hideharu Ogiyama(Itami City Hospital), Yusuke Kato(Niigata University), Mai Horie(Osaka Police Hospital), Takashi Matsunaga(Shiga University of Medical Science), Ryu Ishihara(Osaka International Cancer Institute), Kazuo Kinoshita(Shizuoka University), Takuya Yamada(Osaka International Cancer Institute)
Cited by 91
Related Papers
Activation-Induced Cytidine Deaminase (AID) Deficiency Causes the Autosomal Recessive Form of the Hyper-IgM Syndrome (HIGM2)
|Cell|2000|1.6k
Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images
|Gastric Cancer|2018|742
Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks
|Gastrointestinal Endoscopy|2018|470
Endoscopic submucosal dissection/endoscopic mucosal resection guidelines for esophageal cancer
|Digestive Endoscopy|2020|432