Babak Namazi

583 total citations
17 papers, 351 citations indexed

About

Babak Namazi is a scholar working on Surgery, Oncology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Babak Namazi has authored 17 papers receiving a total of 351 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Surgery, 7 papers in Oncology and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Babak Namazi's work include Surgical Simulation and Training (10 papers), Colorectal Cancer Screening and Detection (6 papers) and Cardiac, Anesthesia and Surgical Outcomes (4 papers). Babak Namazi is often cited by papers focused on Surgical Simulation and Training (10 papers), Colorectal Cancer Screening and Detection (6 papers) and Cardiac, Anesthesia and Surgical Outcomes (4 papers). Babak Namazi collaborates with scholars based in United States, Canada and Iran. Babak Namazi's co-authors include Ganesh Sankaranarayanan, Amin Madani, Daniel A. Hashimoto, Adnan Alseidi, L. Michael Brunt, Allan Okrainec, Maria S. Altieri, Allison Navarrete-Welton, Philip H. Pucher and Venkat Devarajan and has published in prestigious journals such as Annals of Surgery, Journal of Vascular Surgery and Journal of the American College of Surgeons.

In The Last Decade

Babak Namazi

16 papers receiving 345 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Babak Namazi United States 8 221 117 112 90 63 17 351
Armine Vardazaryan France 7 189 0.9× 99 0.8× 106 0.9× 63 0.7× 55 0.9× 11 298
Deepak Alapatt France 8 262 1.2× 129 1.1× 150 1.3× 94 1.0× 66 1.0× 13 412
Caitlin Stafford United States 10 324 1.5× 188 1.6× 77 0.7× 52 0.6× 39 0.6× 31 463
Hiro Hasegawa Japan 12 335 1.5× 231 2.0× 137 1.2× 66 0.7× 84 1.3× 53 488
Joël L. Lavanchy Switzerland 9 266 1.2× 69 0.6× 86 0.8× 39 0.4× 23 0.4× 29 343
Paul Oh United States 8 387 1.8× 48 0.4× 178 1.6× 74 0.8× 69 1.1× 14 495
Jessica H. Nguyen United States 12 309 1.4× 36 0.3× 181 1.6× 103 1.1× 86 1.4× 25 489
Carly R. Garrow Germany 10 387 1.8× 76 0.6× 232 2.1× 47 0.5× 53 0.8× 15 494
Alfonso Lapergola France 12 276 1.2× 98 0.8× 103 0.9× 13 0.1× 45 0.7× 26 407
Matthew H. Lee United States 12 110 0.5× 92 0.8× 112 1.0× 10 0.1× 161 2.6× 31 445

Countries citing papers authored by Babak Namazi

Since Specialization
Citations

This map shows the geographic impact of Babak Namazi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Babak Namazi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Babak Namazi more than expected).

Fields of papers citing papers by Babak Namazi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Babak Namazi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Babak Namazi. The network helps show where Babak Namazi may publish in the future.

Co-authorship network of co-authors of Babak Namazi

This figure shows the co-authorship network connecting the top 25 collaborators of Babak Namazi. A scholar is included among the top collaborators of Babak Namazi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Babak Namazi. Babak Namazi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Abbas, Amr I. Al, Babak Namazi, Patricio M. Polanco, et al.. (2024). The development of a deep learning model for automated segmentation of the robotic pancreaticojejunostomy. Surgical Endoscopy. 38(5). 2553–2561. 2 indexed citations
2.
Müller, F., Pietro Mascagni, Babak Namazi, et al.. (2024). Structured feedback and operative video debriefing with critical view of safety annotation in training of laparoscopic cholecystectomy: a randomized controlled study. Surgical Endoscopy. 38(6). 3241–3252. 2 indexed citations
3.
Bhatia, Manisha, Babak Namazi, Christopher Thomas, et al.. (2023). Use of artificial intelligence to support surgical education personnel shortages in low- and middle-income countries: developing a safer surgeon. Global Surgical Education - Journal of the Association for Surgical Education. 2(1). 2 indexed citations
4.
Li, Allen, Arshia P. Javidan, Babak Namazi, Amin Madani, & Thomas L. Forbes. (2023). Development of an Artificial Intelligence Tool for Intraoperative Guidance During Endovascular Abdominal Aortic Aneurysm Repair. Annals of Vascular Surgery. 99. 96–104. 9 indexed citations
5.
Namazi, Babak, et al.. (2023). Automated segmentation of phases, steps, and tasks in laparoscopic cholecystectomy using deep learning. Surgical Endoscopy. 38(1). 158–170. 11 indexed citations
6.
Namazi, Babak, Daniel A. Hashimoto, Adnan Alseidi, et al.. (2022). Validation of an artificial intelligence platform for the guidance of safe laparoscopic cholecystectomy. Surgical Endoscopy. 37(3). 2260–2268. 35 indexed citations
7.
Li, Allen, Arshia P. Javidan, Babak Namazi, Amin Madani, & Thomas L. Forbes. (2022). Development of an Artificial Intelligence Tool for Intraoperative Guidance During Endovascular Aneurysm Repair. Journal of Vascular Surgery. 76(4). e114–e115.
8.
Namazi, Babak, et al.. (2022). Developing artificial intelligence models for medical student suturing and knot-tying video-based assessment and coaching. Surgical Endoscopy. 37(1). 402–411. 18 indexed citations
9.
Chou, Eric, Chih‐Hung Wang, Babak Namazi, et al.. (2021). Clinical Features of Emergency Department Patients from Early COVID-19 Pandemic that Predict SARS-CoV-2 Infection: Machine-learning Approach. Western Journal of Emergency Medicine. 22(2). 244–251. 8 indexed citations
10.
Namazi, Babak, Ganesh Sankaranarayanan, & Venkat Devarajan. (2021). A contextual detector of surgical tools in laparoscopic videos using deep learning. Surgical Endoscopy. 36(1). 679–688. 27 indexed citations
11.
Namazi, Babak, Amin Madani, Daniel A. Hashimoto, et al.. (2020). AI for Automated Detection of the Establishment of Critical View of Safety in Laparoscopic Cholecystectomy Videos. Journal of the American College of Surgeons. 231(4). e48–e48. 4 indexed citations
12.
Altieri, Maria S., Daniel A. Hashimoto, Babak Namazi, et al.. (2020). Using Artificial Intelligence to Identify Surgical Anatomy, Safe Zones of DISSection, and Dangerous Zones of DISSection during Laparoscopic Cholecystectomy. Journal of the American College of Surgeons. 231(4). e21–e22. 3 indexed citations
13.
Madani, Amin, Babak Namazi, Maria S. Altieri, et al.. (2020). Artificial Intelligence for Intraoperative Guidance. Annals of Surgery. 276(2). 363–369. 208 indexed citations
14.
Namazi, Babak, Ganesh Sankaranarayanan, & Venkat Devarajan. (2019). Attention-Based Surgical Phase Boundaries Detection in Laparoscopic Videos. 577–583. 4 indexed citations
15.
Namazi, Babak, Ganesh Sankaranarayanan, & Venkat Devarajan. (2018). Automatic detection of surgical phases in laparoscopic videos. International Conference on Artificial Intelligence. 124–130. 7 indexed citations
16.
Namazi, Babak & Karim Faez. (2013). Power-aware QoS routing for wireless multimedia sensor networks. 1–5. 3 indexed citations
17.
Namazi, Babak & Karim Faez. (2013). Energy-Efficient Multi-SPEED Routing Protocol For Wireless Sensor Networks. International Journal of Electrical and Computer Engineering (IJECE). 3(2). 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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2026