Didier Mutter
Impact in
- Health Informatics top 0.5%
- Surgery top 0.5%
- Surgical Simulation and Training
- Minimally Invasive Surgical Techniques
Papers in
- Co-authors
- Jacques Marescaux (169 shared papers)Joël Leroy (28 shared papers)Nicolas Padoy (23 shared papers)Michel Vix (35 shared papers)Luc Soler (20 shared papers)Andru Putra Twinanda (2 shared papers)Michel de Mathelin (2 shared papers)Michèle Diana (30 shared papers)
- Journals
- Surgical Endoscopy (31 papers)Surgical Innovation (10 papers)Annals of Surgery (9 papers)British journal of surgery (7 papers)World Journal of Surgery (6 papers)
- Partner nations
- FranceItalySwitzerland
In The Last Decade
Didier Mutter
219 papers receiving 6.3k citations
Didier Mutter's Hit Papers
Peers
Comparison fields: 5 of 163
- Health Informatics 217
- Surgery 4.4k
- Hepatology 572
- Oncology 1.9k
- Computer Vision and Pattern Recognition 994
Countries citing papers authored by Didier Mutter
This map shows the geographic impact of Didier Mutter'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 Didier Mutter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Didier Mutter more than expected).
Fields of papers citing papers by Didier Mutter
This network shows the impact of papers produced by Didier Mutter. 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 Didier Mutter. The network helps show where Didier Mutter may publish in the future.
Co-authors
The 25 scholars most cited alongside Didier Mutter, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 230 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos Hit paper breakdown → | 2016 | 579 |
| 2 | 2002 | 347 | |
| 3 | 2004 | 302 | |
| 4 | 2002 | 299 | |
| 5 | 2011 | 251 | |
| 6 | 1998 | 195 | |
| 7 | 2001 | 182 | |
| 8 | 2001 | 170 | |
| 9 | 2020 | 166 | |
| 10 | 2005 | 132 | |
| 11 | 1996 | 107 | |
| 12 | 2012 | 106 | |
| 13 | 2016 | 101 | |
| 14 | 2009 | 95 | |
| 15 | 2011 | 93 | |
| 16 | 2022 | 90 | |
| 17 | 2019 | 88 | |
| 18 | 2011 | 82 | |
| 19 | 1998 | 79 | |
| 20 | 2015 | 78 |
About Didier Mutter
Didier Mutter is a scholar working on Surgery, Oncology, Pulmonary and Respiratory Medicine, Biomedical Engineering and Radiology, Nuclear Medicine and Imaging, having authored 230 papers that have together received 6.6k indexed citations. Recurring topics across this work include Surgical Simulation and Training (39 papers), Colorectal Cancer Surgical Treatments (29 papers), Gallbladder and Bile Duct Disorders (24 papers), Pancreatic and Hepatic Oncology Research (22 papers), Colorectal Cancer Screening and Detection (19 papers), Hepatocellular Carcinoma Treatment and Prognosis (18 papers), Anatomy and Medical Technology (17 papers) and Diverticular Disease and Complications (16 papers). The work is most often cited by research in Health Informatics (217 citations), Surgery (4.4k citations), Hepatology (572 citations), Oncology (1.9k citations) and Computer Vision and Pattern Recognition (994 citations). Didier Mutter has collaborated with scholars based in France, Italy and Switzerland. Frequent co-authors include Jacques Marescaux, Joël Leroy, Nicolas Padoy, Michel Vix, Luc Soler, Andru Putra Twinanda, Michel de Mathelin, Michèle Diana, Patrick Pessaux and Francesco Rubino. Their work appears in journals such as Surgical Endoscopy, Surgical Innovation, Annals of Surgery, British journal of surgery and World Journal of Surgery.
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.