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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Computer Vision Analysis of Intraoperative Video
Daniel A. Hashimoto, Guy Rosman, Elan R. Witkowski, et al.
Annals of Surgery (2019) Vol. 270, Iss. 3, pp. 414-421
Open Access | Times Cited: 241

Showing 1-25 of 241 citing articles:

Machine Learning for Surgical Phase Recognition
Carly R. Garrow, Karl‐Friedrich Kowalewski, Linhong Li, et al.
Annals of Surgery (2020) Vol. 273, Iss. 4, pp. 684-693
Open Access | Times Cited: 203
Artificial Intelligence for Surgical Safety
Pietro Mascagni, Armine Vardazaryan, Deepak Alapatt, et al.
Annals of Surgery (2020) Vol. 275, Iss. 5, pp. 955-961
Closed Access | Times Cited: 187
The potential of artificial intelligence to improve patient safety: a scoping review
David W. Bates, David M. Levine, Ania Syrowatka, et al.
npj Digital Medicine (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 175
Artificial Intelligence Surgery: How Do We Get to Autonomous Actions in Surgery?
Andrew A. Gumbs, Isabella Frigerio, Gaya Spolverato, et al.
Sensors (2021) Vol. 21, Iss. 16, pp. 5526-5526
Open Access | Times Cited: 116
Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward
Eyad Elyan, Pattaramon Vuttipittayamongkol, Pamela Johnston, et al.
Artificial Intelligence Surgery (2022)
Open Access | Times Cited: 89
Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark
Martin Wagner, Beat P. Müller‐Stich, Anna Kisilenko, et al.
Medical Image Analysis (2023) Vol. 86, pp. 102770-102770
Open Access | Times Cited: 49
Current and future applications of artificial intelligence in surgery: implications for clinical practice and research
Miranda X. Morris, Davide Fiocco, Tommaso Caneva, et al.
Frontiers in Surgery (2024) Vol. 11
Open Access | Times Cited: 18
Computer vision in surgery
Thomas M. Ward, Pietro Mascagni, Yutong Ban, et al.
Surgery (2020) Vol. 169, Iss. 5, pp. 1253-1256
Closed Access | Times Cited: 121
Automated laparoscopic colorectal surgery workflow recognition using artificial intelligence: Experimental research
Daichi Kitaguchi, Nobuyoshi Takeshita, Hiroki Matsuzaki, et al.
International Journal of Surgery (2020) Vol. 79, pp. 88-94
Open Access | Times Cited: 101
Deep learning visual analysis in laparoscopic surgery: a systematic review and diagnostic test accuracy meta-analysis
Roi Anteby, Nir Horesh, Shelly Soffer, et al.
Surgical Endoscopy (2021) Vol. 35, Iss. 4, pp. 1521-1533
Closed Access | Times Cited: 85
A Computer Vision Platform to Automatically Locate Critical Events in Surgical Videos
Pietro Mascagni, Deepak Alapatt, Takeshi Urade, et al.
Annals of Surgery (2021) Vol. 274, Iss. 1, pp. e93-e95
Closed Access | Times Cited: 66
Artificial intelligence‐based computer vision in surgery: Recent advances and future perspectives
Daichi Kitaguchi, Nobuyoshi Takeshita, Hiro Hasegawa, et al.
Annals of Gastroenterological Surgery (2021) Vol. 6, Iss. 1, pp. 29-36
Open Access | Times Cited: 64
SAGES consensus recommendations on an annotation framework for surgical video
Ozanan R. Meireles, Guy Rosman, Maria S. Altieri, et al.
Surgical Endoscopy (2021) Vol. 35, Iss. 9, pp. 4918-4929
Open Access | Times Cited: 63
Surgical data science and artificial intelligence for surgical education
Thomas M. Ward, Pietro Mascagni, Amin Madani, et al.
Journal of Surgical Oncology (2021) Vol. 124, Iss. 2, pp. 221-230
Closed Access | Times Cited: 56
Deep Learning Applications in Surgery: Current Uses and Future Directions
Miranda X. Morris, Aashish Rajesh, Malke Asaad, et al.
The American Surgeon (2022) Vol. 89, Iss. 1, pp. 36-42
Closed Access | Times Cited: 41
Evolution of the digital operating room: the place of video technology in surgery
Samy Cheikh Youssef, Kaled Haram, Jonathan Noël, et al.
Langenbeck s Archives of Surgery (2023) Vol. 408, Iss. 1
Open Access | Times Cited: 23
Current and Future Advances in Surgical Therapy for Pituitary Adenoma
Danyal Z. Khan, John Hanrahan, Stephanie Baldeweg, et al.
Endocrine Reviews (2023) Vol. 44, Iss. 5, pp. 947-959
Open Access | Times Cited: 23
Surgical training simulation modalities in minimally invasive surgery: How to achieve evidence-based curricula by translational research
Philipp Seeger, Nikolaos Kaldis, Felix Nickel, et al.
The American Journal of Surgery (2025) Vol. 242, pp. 116197-116197
Open Access | Times Cited: 1
Impact of data on generalization of AI for surgical intelligence applications
Omri Bar, Daniel Neimark, Maya Zohar, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 68
Automated operative phase identification in peroral endoscopic myotomy
Thomas M. Ward, Daniel A. Hashimoto, Yutong Ban, et al.
Surgical Endoscopy (2020) Vol. 35, Iss. 7, pp. 4008-4015
Open Access | Times Cited: 67
The Role of Artificial Intelligence in Surgery
Daniel A. Hashimoto, Thomas M. Ward, Ozanan R. Meireles
Advances in Surgery (2020) Vol. 54, pp. 89-101
Closed Access | Times Cited: 60
Artificial intelligence-based automated laparoscopic cholecystectomy surgical phase recognition and analysis
Ke Cheng, Jiaying You, Shangdi Wu, et al.
Surgical Endoscopy (2021) Vol. 36, Iss. 5, pp. 3160-3168
Closed Access | Times Cited: 54
A Review on the Current Applications of Artificial Intelligence in the Operating Room
David C. Birkhoff, Anne Sophie H.M. van Dalen, Marlies P. Schijven
Surgical Innovation (2021) Vol. 28, Iss. 5, pp. 611-619
Open Access | Times Cited: 53
Artificial Intelligence in Brain Tumour Surgery—An Emerging Paradigm
Simon C. Williams, Hugo Layard Horsfall, Jonathan P. Funnell, et al.
Cancers (2021) Vol. 13, Iss. 19, pp. 5010-5010
Open Access | Times Cited: 53
Automated segmentation by deep learning of loose connective tissue fibers to define safe dissection planes in robot-assisted gastrectomy
Yuta Kumazu, Nao Kobayashi, Naoki Kitamura, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 49
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