Artificial intelligence-assisted analysis of endoscopic retrograde cholangiopancreatography image for identifying ampulla and difficulty of selective cannulation
Abstract The advancement of artificial intelligence (AI) has facilitated its application in medical fields. However, there has been little research for AI-assisted endoscopy, despite the clinical significance of the efficiency and safety of cannulation in the endoscopic retrograde cholangiopancreato...
Saved in:
Main Authors: | Taesung Kim, Jinhee Kim, Hyuk Soon Choi, Eun Sun Kim, Bora Keum, Yoon Tae Jeen, Hong Sik Lee, Hoon Jai Chun, Sung Yong Han, Dong Uk Kim, Soonwook Kwon, Jaegul Choo, Jae Min Lee |
---|---|
Format: | article |
Language: | EN |
Published: |
Nature Portfolio
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/7faffbe01bd3449bbde1be6039f54e82 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The radiation environment of anaesthesiologists in the endoscopic retrograde cholangiopancreatography room
by: Bora Lee, et al.
Published: (2019) -
Risk Factors for Post Endoscopic Retrograde Cholangiopancreatography Pancreatitis and Hyperamylasemia
by: J Shokry Shirvany,, et al.
Published: (2011) -
Recent advances in prevention and management of endoscopic retrograde cholangiopancreatography-related duodenal perforation
by: Guiying Zhu, et al.
Published: (2020) -
Missing Value Imputation of Time-Series Air-Quality Data via Deep Neural Networks
by: Taesung Kim, et al.
Published: (2021) -
Evaluation of bispectral index monitoring efficacy in endoscopic patients who underwent retrograde cholangiopancreatography and received sedoanalgesia
by: Ferda Inal, et al.
Published: (2020)