Most cited papers from Docbot (United States)
What are the most cited papers from Docbot (United States)?
The most cited paper from Docbot (United States) is "Artificial intelligence using convolutional neural networks for real-time detection of early esophageal neoplasia in Barrett’s esophagus (with video)" (Rintaro Hashimoto, James Requa, Tyler Dao et al., 2020), with 233 citations. Next come "Central Reading of Ulcerative Colitis Clinical Trial Videos Using Neural Networks" (138) and "Prediction of Polyp Pathology Using Convolutional Neural Networks Achieves “Resect and Discard” Thresholds" (123).
Showing 13 of 13 papers. Every paper is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | Artificial intelligence using convolutional neural networks for real-time detection of early esophageal neoplasia in Barrett’s esophagus (with video) Rintaro Hashimoto, James Requa, Tyler Dao et al. · Gastrointestinal Endoscopy | 10 Jan 2020 | 233 |
| 2 | Central Reading of Ulcerative Colitis Clinical Trial Videos Using Neural Networks Klaus T. Gottlieb, James Requa, William E. Karnes et al. · Gastroenterology | 21 Oct 2020 | 138 |
| 3 | Prediction of Polyp Pathology Using Convolutional Neural Networks Achieves “Resect and Discard” Thresholds Robin Zachariah, Jason Samarasena, Daniel G. Luba et al. · The American Journal of Gastroenterology | 23 Oct 2019 | 123 |
| 4 | Artificial intelligence for the assessment of bowel preparation Ji Young Lee, Audrey H. Calderwood, William E. Karnes et al. · Gastrointestinal Endoscopy | 8 Dec 2021 | 50 |
| 5 | Proceedings from the First Global Artificial Intelligence in Gastroenterology and Endoscopy Summit Sravanthi Parasa et al. · Gastrointestinal Endoscopy | 27 Apr 2020 | 45 |
| 6 | DoraPicker: An autonomous picking system for general objects Hao Ran Zhang, Pinxin Long, Dandan Zhou et al. | Aug 2016 | 32 |
| 7 | Artificial Intelligence Can Accurately Detect Tools Used During Colonoscopy: Another Step Forward Toward Autonomous Report Writing: Presidential Poster Award Jason Samarasena, Allen R. Yu, Ericson John Torralba et al. · The American Journal of Gastroenterology | Oct 2018 | 9 |
| 8 | Artificial intelligence for colon polyp detection: Why should we embrace this? Robin Zachariah, Andrew Q. Ninh, William E. Karnes · Techniques and Innovations in Gastrointestinal Endoscopy | 11 Oct 2019 | 3 |
| 9 | Highly Sensitive and Specific Identification of Anatomical Landmarks and Mucosal Abnormalities in Video Capsule Endoscopy With Convolutional Neural Networks: Presidential Poster Award Felix H. Lui, Yash Rusconi-Rodrigues, Andrew Q. Ninh et al. · The American Journal of Gastroenterology | Oct 2018 | 3 |
| 10 | Adenoma Detection Through Deep Learning: 2017 Presidential Poster Award William E. Karnes, Andrew Q. Ninh, Gregor Urban et al. · The American Journal of Gastroenterology | Oct 2017 | 3 |
| 11 | Embedding High-Level Knowledge into DQNs to Learn Faster and More Safely Zihang Gao, Fangzhen Lin, Yi Zhou et al. · Proceedings of the AAAI Conference on Artificial Intelligence | 3 Apr 2020 | 1 |
| 12 | 265 Beyond Polyp Detection: Novel Method to Track Individual Polyps Using Neural Networks James Requa, Tyler Dao, Andrew Q. Ninh et al. · The American Journal of Gastroenterology | Oct 2019 | 0 |
| 13 | In-hand Sliding Regrasp with Spring-Sliding Compliance Jian Hong Shi, Kevin Lynch · arXiv (Cornell University) | 22 Sep 2019 | 0 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.