Jan Egger

190 papers receiving 3.8k citations

Jan Egger's Hit Papers

Benefits, limits, and risks of ChatGPT in medicine 2025 · 36 citations
360+1Years since publication50100150200

Peers

Jan Egger
Comparison fields: 5 of 172
  • Health Informatics 322
  • Oral Surgery 400
  • Computer Vision and Pattern Recognition 1.0k
  • Radiology, Nuclear Medicine and Imaging 692
  • Human-Computer Interaction 187
Replace Pierre Jannin with:
Pierre Jannin France
Ching‐Wei Wang Taiwan
Bulat Ibragimov Denmark
Serena Yeung-Levy United States
Peter Kazanzides United States
Leo Joskowicz Israel
Gábor Fichtinger Canada
S. M. Reza Soroushmehr United States
Nobuhiko Hata United States
Örjan Smedby Sweden
Jan Egger relative to Pierre Jannin France Pierre Jannin's profile →
Citations per field
00.5×2×4×6.6×
Pierre Jannin · 1×
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 203 papers — load more, or switch the sort, to bring in the rest.

#Work
1
ChatGPT in healthcare: A taxonomy and systematic review
Hit paper breakdown →
2024219
2 2013197
3 2020193
4 2022180
5 2015169
6
CellViT: Vision Transformers for precise cell segmentation and classification
Hit paper breakdown →
2024161
7 202388
8 201780
9 202070
10 201270
11 201267
12 201964
13 202063
14 201454
15 201751
16 202150
17 201849
18 202147
19 201145
20 202345

About Jan Egger

Jan Egger is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Oral Surgery, Biomedical Engineering and Surgery, having authored 203 papers that have together received 3.9k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (33 papers), Radiomics and Machine Learning in Medical Imaging (31 papers), Anatomy and Medical Technology (26 papers), Medical Imaging and Analysis (22 papers), Augmented Reality Applications (21 papers), AI in cancer detection (20 papers), Aortic aneurysm repair treatments (18 papers) and Surgical Simulation and Training (17 papers). The work is most often cited by research in Health Informatics (322 citations), Oral Surgery (400 citations), Computer Vision and Pattern Recognition (1.0k citations), Radiology, Nuclear Medicine and Imaging (692 citations) and Human-Computer Interaction (187 citations). Jan Egger has collaborated with scholars based in Germany, Austria and United States. Frequent co-authors include Xiaojun Chen, Jens Kleesiek, Christina Gsaxner, Jianning Li, Christopher Nimsky, Bernd Freisleben, Antonio Pepe, Dieter Schmalstieg, Tina Kapur and Jürgen Wallner. Their work appears in journals such as PLoS ONE, Computer Methods and Programs in Biomedicine, Medical Image Analysis, Scientific Reports and Computerized Medical Imaging and Graphics.

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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