Jan Egger

153 papers receiving 2.9k citations

Jan Egger's Hit Papers

Benefits, limits, and risks of ChatGPT in medicine 2025 · 22 citations
220+1Years since publication50100150

Peers

Jan Egger
Comparison fields: 5 of 167
  • Health Informatics 260
  • Oral Surgery 395
  • Computer Vision and Pattern Recognition 898
  • Human-Computer Interaction 183
  • Radiology, Nuclear Medicine and Imaging 769
Replace Pierre Jannin with:
Pierre Jannin France
Peter Kazanzides United States
Bulat Ibragimov Denmark
Leo Joskowicz Israel
Nobuhiko Hata United States
Didier Mutter France
Gábor Fichtinger Canada
Mauricio Reyes Switzerland
Ken Masamune Japan
Ulaş Bağcı United States
Jan Egger relative to Pierre Jannin France Pierre Jannin's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jan Egger

Since Specialization
Citations

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

Fields of papers citing papers by Jan Egger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 164 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013190
2
ChatGPT in healthcare: A taxonomy and systematic review
Hit paper breakdown →
2024171
3 2020163
4 2022153
5 2015152
6
CellViT: Vision Transformers for precise cell segmentation and classification
Hit paper breakdown →
202496
7 201777
8 202371
9 201269
10 201262
11 201956
12 202052
13 201451
14 202050
15 201843
16 201240
17 202140
18 201139
19 201239
20 201736

About Jan Egger

Jan Egger is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Surgery and Oral Surgery, having authored 164 papers that have together received 2.9k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (33 papers), Medical Image Segmentation Techniques (31 papers), Anatomy and Medical Technology (28 papers), Medical Imaging and Analysis (23 papers), Dental Radiography and Imaging (20 papers), AI in cancer detection (19 papers), Surgical Simulation and Training (17 papers) and Aortic aneurysm repair treatments (17 papers). The work is most often cited by research in Health Informatics (260 citations), Oral Surgery (395 citations), Computer Vision and Pattern Recognition (898 citations), Human-Computer Interaction (183 citations) and Radiology, Nuclear Medicine and Imaging (769 citations). Jan Egger has collaborated with scholars based in Germany, Austria and China. Frequent co-authors include Jianning Li, Xiaojun Chen, Christina Gsaxner, Christopher Nimsky, Jens Kleesiek, Bernd Freisleben, Antonio Pepe, Tina Kapur, Jürgen Wallner and Dieter Schmalstieg. Their work appears in journals such as PLoS ONE, Medical Image Analysis, Computer Methods and Programs in Biomedicine, Scientific Reports and Scientific Data.

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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