Methodology to develop machine learning algorithms to improve performance in gastrointestinal endoscopy-Reference-Cited by-同舟云学术

Methodology to develop machine learning algorithms to improve performance in gastrointestinal endoscopy

Published:2018-12-07 Issue:45 Volume:24 Page:5057-5062
ISSN:1007-9327
Container-title:World Journal of Gastroenterology
language:
Short-container-title:WJG

Author:

Lange Thomas de,Halvorsen Pål,Riegler Michael

Publisher

Baishideng Publishing Group Inc.

Subject

Gastroenterology,General Medicine

Reference45 articles.

1. Colorectal cancer

2. World Health Organization - International Agency for Research on Cancer. Estimated cancer incidence, mortality and prevalence world-wide in 2012. Available from: URL: http://globocan.iarc.fr/Default.aspx. 2012

3. Global cancer statistics, 2012

4. Efficacy and Effectiveness of Colonoscopy: How Do We Bridge the Gap?

5. Endoscopic Experience Improves Interobserver Agreement in the Grading of Esophagitis by Los Angeles Classification: Conventional Endoscopy and Optimal Band Image System

Cited by 31 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Colorectal white light filter object detection based on improved YOLOv5;International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023);2024-03-27

2. Artificial intelligence in gastrointestinal endoscopy: a comprehensive review;Annals of Gastroenterology;2024

3. Improving Endoscopic Image Analysis: Attention Mechanism Integration in Grid Search Fine-Tuned Transfer Learning Model for Multi-Class Gastrointestinal Disease Classification;IEEE Access;2024

4. Convolution Neural Network for Gastrointestinal Cancer Detection and Classification using Deep Learning;2023 International Conference on System, Computation, Automation and Networking (ICSCAN);2023-11-17

5. UY-NET: A Two-Stage Network to Improve the Result of Detection in Colonoscopy Images;Applied Sciences;2023-09-28