Jan Egger
Impact in
- Health Informatics top 0.2%
- Oral Surgery top 1%
- Dental Radiography and Imaging
Papers in
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- Medical Image Segmentation Techniques 36
- Augmented Reality Applications 22
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- Anatomy and Medical Technology 31
- Medical Imaging and Analysis 25
- Co-authors
- Christina Gsaxner (57 shared papers)Jianning Li (43 shared papers)Xiaojun Chen (32 shared papers)Antonio Pepe (44 shared papers)Christopher Nimsky (23 shared papers)Jens Kleesiek (44 shared papers)Bernd Freisleben (28 shared papers)Jürgen Wallner (28 shared papers)
In The Last Decade
Jan Egger
185 papers receiving 3.6k citations
Jan Egger's Hit Papers
Peers
Comparison fields: 5 of 168
- Health Informatics 285
- Oral Surgery 419
- Computer Vision and Pattern Recognition 1.1k
- Radiology, Nuclear Medicine and Imaging 703
- Human-Computer Interaction 182
Countries citing papers authored by Jan Egger
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
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.
All Works
Showing the 20 most-cited of 206 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 200 | |
| 2 | ChatGPT in healthcare: A taxonomy and systematic review Hit paper breakdown → | 2024 | 190 |
| 3 | 2020 | 173 | |
| 4 | 2022 | 170 | |
| 5 | 2015 | 167 | |
| 6 | CellViT: Vision Transformers for precise cell segmentation and classification Hit paper breakdown → | 2024 | 125 |
| 7 | 2017 | 83 | |
| 8 | 2023 | 79 | |
| 9 | 2012 | 70 | |
| 10 | 2020 | 68 | |
| 11 | 2012 | 65 | |
| 12 | 2019 | 65 | |
| 13 | 2020 | 59 | |
| 14 | 2014 | 55 | |
| 15 | 2021 | 49 | |
| 16 | 2018 | 48 | |
| 17 | 2017 | 47 | |
| 18 | 2022 | 45 | |
| 19 | 2021 | 45 | |
| 20 | 2012 | 42 |
About Jan Egger
Jan Egger is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, Surgery and Pulmonary and Respiratory Medicine, having authored 206 papers that have together received 3.7k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (36 papers), Radiomics and Machine Learning in Medical Imaging (33 papers), Anatomy and Medical Technology (31 papers), Medical Imaging and Analysis (25 papers), Augmented Reality Applications (22 papers), AI in cancer detection (21 papers), Dental Radiography and Imaging (20 papers) and Aortic aneurysm repair treatments (20 papers). The work is most often cited by research in Health Informatics (285 citations), Oral Surgery (419 citations), Computer Vision and Pattern Recognition (1.1k citations), Radiology, Nuclear Medicine and Imaging (703 citations) and Human-Computer Interaction (182 citations). Jan Egger has collaborated with scholars based in Germany, Austria and China. Frequent co-authors include Christina Gsaxner, Jianning Li, Xiaojun Chen, Antonio Pepe, Christopher Nimsky, Jens Kleesiek, Bernd Freisleben, Jürgen Wallner, Dieter Schmalstieg and Tina Kapur. Their work appears in journals such as PLoS ONE, Scientific Reports, Computer Methods and Programs in Biomedicine, Medical Image Analysis and Data in Brief.
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.