Mika Sinanan

5.4k citations
80 papers · 3.9k indexed · h-index 34

Impact in

  • Surgery top 1%
    • Surgical Simulation and Training
    • Pancreatitis Pathology and Treatment
    • Gastrointestinal disorders and treatments
    • Soft Robotics and Applications
    • Anatomy and Medical Technology

Papers in

Mika Sinanan

80 papers receiving 3.7k citations

Peers

Mika Sinanan
Comparison fields: 5 of 134
  • Surgery 2.7k
  • Biomedical Engineering 1.8k
  • Gastroenterology 181
  • Computer Vision and Pattern Recognition 654
  • Oncology 587
Replace Jenny Dankelman with:
Jenny Dankelman Netherlands
Joël Leroy France
Kevin Cleary United States
Dmitry Oleynikov United States
Michel de Mathelin France
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Fernando Bello United Kingdom
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Mika Sinanan relative to Jenny Dankelman Netherlands Jenny Dankelman's profile →
Citations per field
00.5×2.6×
Jenny Dankelman · 1×
Citations per year

Countries citing papers authored by Mika Sinanan

Since Specialization
Citations

This map shows the geographic impact of Mika Sinanan'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 Mika Sinanan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mika Sinanan more than expected).

Fields of papers citing papers by Mika Sinanan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mika Sinanan. 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 Mika Sinanan. The network helps show where Mika Sinanan may publish in the future.

Co-authors

The 25 scholars most cited alongside Mika Sinanan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mika Sinanan Line = papers co-authored together Mika Sinanan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998340
2 1999249
3 2001209
4 2009188
5 2008170
6 2006169
7 2006135
8 2001128
9 2013119
10 2000119
11 2003119
12 2003118
13 2007110
14 1996108
15 200396
16 200790
17 200290
18 200280
19 200177
20 200473

About Mika Sinanan

Mika Sinanan is a scholar working on Surgery, Biomedical Engineering, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine and Cardiology and Cardiovascular Medicine, having authored 80 papers that have together received 3.9k indexed citations. Recurring topics across this work include Surgical Simulation and Training (35 papers), Soft Robotics and Applications (23 papers), Anatomy and Medical Technology (21 papers), Augmented Reality Applications (15 papers), Cardiac, Anesthesia and Surgical Outcomes (10 papers), Pancreatic and Hepatic Oncology Research (6 papers), Teleoperation and Haptic Systems (5 papers) and Robotic Mechanisms and Dynamics (5 papers). The work is most often cited by research in Surgery (2.7k citations), Biomedical Engineering (1.8k citations), Gastroenterology (181 citations), Computer Vision and Pattern Recognition (654 citations) and Oncology (587 citations). Mika Sinanan has collaborated with scholars based in United States, Netherlands and Russia. Frequent co-authors include Blake Hannaford, Jacob Rosén, Carlos A. Pellegrini, Jeffrey D. Brown, Lily Chang, Mark Macfarlane, Christina Richards, Mitchell J. H. Lum, Ellen Hauptmann and Patrick C. Freeny. Their work appears in journals such as The American Journal of Surgery, Surgical Endoscopy, IEEE Transactions on Biomedical Engineering, Gastroenterology and The International Journal of Robotics Research.

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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