Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

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

Showing 1-25 of 187 citing articles:

Surgical data science – from concepts toward clinical translation
Lena Maier‐Hein, Matthias Eisenmann, Duygu Sarıkaya, et al.
Medical Image Analysis (2021) Vol. 76, pp. 102306-102306
Open Access | Times Cited: 220
Rendezvous: Attention mechanisms for the recognition of surgical action triplets in endoscopic videos
Chinedu Innocent Nwoye, Tong Yu, Cristians González, et al.
Medical Image Analysis (2022) Vol. 78, pp. 102433-102433
Open Access | Times Cited: 96
Computer vision in surgery: from potential to clinical value
Pietro Mascagni, Deepak Alapatt, Luca Sestini, et al.
npj Digital Medicine (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 91
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: 120
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: 64
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: 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
Federated Cycling (FedCy): Semi-Supervised Federated Learning of Surgical Phases
Hasan Kassem, Deepak Alapatt, Pietro Mascagni, et al.
IEEE Transactions on Medical Imaging (2022) Vol. 42, Iss. 7, pp. 1920-1931
Open Access | Times Cited: 39
Automatic Surgical Skill Assessment System Based on Concordance of Standardized Surgical Field Development Using Artificial Intelligence
Takahiro Igaki, Daichi Kitaguchi, Hiroki Matsuzaki, et al.
JAMA Surgery (2023) Vol. 158, Iss. 8, pp. e231131-e231131
Closed Access | Times Cited: 33
Can surgeons trust AI? Perspectives on machine learning in surgery and the importance of eXplainable Artificial Intelligence (XAI)
Johanna M. Brandenburg, Beat P. Müller‐Stich, Martin Wagner, et al.
Langenbeck s Archives of Surgery (2025) Vol. 410, Iss. 1
Open Access | Times Cited: 1
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
Intraoperative video analysis and machine learning models will change the future of surgical training
Michal Kawka, Tamara Gall, Chihua Fang, et al.
Intelligent Surgery (2021) Vol. 1, pp. 13-15
Open Access | Times Cited: 44
The Advances in Computer Vision That Are Enabling More Autonomous Actions in Surgery: A Systematic Review of the Literature
Andrew A. Gumbs, Vincent Grasso, Nicolas Bourdel, et al.
Sensors (2022) Vol. 22, Iss. 13, pp. 4918-4918
Open Access | Times Cited: 37
Validation of an artificial intelligence platform for the guidance of safe laparoscopic cholecystectomy
Simon Laplante, Babak Namazi, Parmiss Kiani, et al.
Surgical Endoscopy (2022) Vol. 37, Iss. 3, pp. 2260-2268
Closed Access | Times Cited: 34
Artificial Intelligence in Colorectal Cancer Surgery: Present and Future Perspectives
Giuseppe Quero, Pietro Mascagni, Fiona R. Kolbinger, et al.
Cancers (2022) Vol. 14, Iss. 15, pp. 3803-3803
Open Access | Times Cited: 29
Artificial intelligence for phase recognition in complex laparoscopic cholecystectomy
Tomer Golany, Amit Aides, Daniel Z. Freedman, et al.
Surgical Endoscopy (2022) Vol. 36, Iss. 12, pp. 9215-9223
Open Access | Times Cited: 28
Artificial intelligence and surgery
Masashi Takeuchi, Yuko Kitagawa
Annals of Gastroenterological Surgery (2023) Vol. 8, Iss. 1, pp. 4-5
Open Access | Times Cited: 20
Deep learning-based recognition of key anatomical structures during robot-assisted minimally invasive esophagectomy
R. B. den Boer, Tim J. M. Jaspers, C. de Jongh, et al.
Surgical Endoscopy (2023) Vol. 37, Iss. 7, pp. 5164-5175
Open Access | Times Cited: 19
The Role of Artificial Intelligence on Tumor Boards: Perspectives from Surgeons, Medical Oncologists and Radiation Oncologists
Valerio Nardone, Federica Marmorino, Marco Maria Germani, et al.
Current Oncology (2024) Vol. 31, Iss. 9, pp. 4984-5007
Open Access | Times Cited: 7
Team dynamics in emergency surgery teams: results from a first international survey
Lorenzo Cobianchi, Francesca Dal Mas, Maurizio Massaro, et al.
World Journal of Emergency Surgery (2021) Vol. 16, Iss. 1
Open Access | Times Cited: 39
Artificial intelligence software available for medical devices: surgical phase recognition in laparoscopic cholecystectomy
Ken’ichi Shinozuka, Sayaka Turuda, Atsuro Fujinaga, et al.
Surgical Endoscopy (2022) Vol. 36, Iss. 10, pp. 7444-7452
Open Access | Times Cited: 26
Knowledge, attitude, and practice of artificial intelligence in emergency and trauma surgery, the ARIES project: an international web-based survey
Belinda De Simone, Fikri M. Abu‐Zidan, Andrew A. Gumbs, et al.
World Journal of Emergency Surgery (2022) Vol. 17, Iss. 1
Open Access | Times Cited: 23
Real-time detection of the recurrent laryngeal nerve in thoracoscopic esophagectomy using artificial intelligence
Kazuma Sato, Takeo Fujita, Hiroki Matsuzaki, et al.
Surgical Endoscopy (2022) Vol. 36, Iss. 7, pp. 5531-5539
Closed Access | Times Cited: 22
Early-stage clinical evaluation of real-time artificial intelligence assistance for laparoscopic cholecystectomy
Pietro Mascagni, Deepak Alapatt, Alfonso Lapergola, et al.
British journal of surgery (2023) Vol. 111, Iss. 1
Closed Access | Times Cited: 15
Page 1 - Next Page

Scroll to top