P Vávra

57 papers receiving 733 citations

Peers

P Vávra
Comparison fields: 5 of 99
  • Health Informatics 10
  • Hepatology 54
  • Surgery 271
  • Computer Vision and Pattern Recognition 142
  • Human-Computer Interaction 34
Replace P Zonča with:
P Zonča Czechia
Ahmed El‐Gendi Egypt
Didier Mutter France
Maki Sugimoto Japan
Didier Mutter France
Asaki Hattori Japan
Hannes Kenngott Germany
Matthias Peterhans Switzerland
Emmanuel Wilson United States
Yukio Oshiro Japan
P Vávra relative to P Zonča Czechia P Zonča's profile →
Citations per field
00.5×1.5×
P Zonča · 1×
Citations per year

Countries citing papers authored by P Vávra

Since Specialization
Citations

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

Fields of papers citing papers by P Vávra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside P Vávra, 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 P Vávra Line = papers co-authored together P Vávra links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017280
2 201684
3 200540
4 201539
5 200829
6 200828
7 201724
8 201418
9 200917
10 201717
11 201611
12 201111
13 201511
14 201210
15 20199
16 20098
17 20217
18 20147
19
3D high resolution anorectal manometry in functional anorectal evaluation.
20147
20 20116

About P Vávra

P Vávra is a scholar working on Surgery, Hepatology, Pulmonary and Respiratory Medicine, Oncology and Cardiology and Cardiovascular Medicine, having authored 68 papers that have together received 749 indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (11 papers), Colorectal Cancer Surgical Treatments (6 papers), Liver Disease Diagnosis and Treatment (5 papers), Pelvic floor disorders treatments (5 papers), Diverticular Disease and Complications (4 papers), Colorectal Cancer Treatments and Studies (3 papers), Ultrasound and Hyperthermia Applications (3 papers) and Cardiac electrophysiology and arrhythmias (2 papers). The work is most often cited by research in Health Informatics (10 citations), Hepatology (54 citations), Surgery (271 citations), Computer Vision and Pattern Recognition (142 citations) and Human-Computer Interaction (34 citations). P Vávra has collaborated with scholars based in Czechia, United Kingdom and Slovakia. Frequent co-authors include Peter Ihnát, P Zonča, Nagy Habib, Jan Roman, Ahmed El‐Gendi, L Martínek, M Peteja, Shirin Elizabeth Khorsandi, Dimitris Zacharoulis and Giuseppe Navarra. Their work appears in journals such as World Journal of Gastroenterology, Sensors and Actuators B Chemical, BioMed Research International, Archives of Gerontology and Geriatrics and Obesity 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.

Explore authors with similar magnitude of impact