Christian Leibig
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Health Informatics top 1%
- Computer Vision and Pattern Recognition
- Oncology
- Co-authors
- Siegfried WahlPhilipp BerensVaneeda AllkenMurat Seçkin AyhanLale UmutluKatja PinkerGünther ZeckThomas Wächtler
- Topics
- Radiomics and Machine Learning in Medical Imaging (5 papers)AI in cancer detection (5 papers)Global Cancer Incidence and Screening (3 papers)
- Partner nations
- GermanySwitzerlandAustria
In The Last Decade
Christian Leibig
10 papers receiving 471 citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Artificial Intelligence 270
- Radiology, Nuclear Medicine and Imaging 206
- Health Informatics 106
- Computer Vision and Pattern Recognition 44
- Oncology 44
Countries citing papers authored by Christian Leibig
This map shows the geographic impact of Christian Leibig'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 Christian Leibig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christian Leibig more than expected).
Fields of papers citing papers by Christian Leibig
This network shows the impact of papers produced by Christian Leibig. 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 Christian Leibig. The network helps show where Christian Leibig may publish in the future.
Co-authorship network of co-authors of Christian Leibig
This figure shows the co-authorship network connecting the top 25 collaborators of Christian Leibig. A scholar is included among the top collaborators of Christian Leibig based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Christian Leibig. Christian Leibig is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Nationwide real-world implementation of AI for cancer detection in population-based mammography screeningbreakdown → | 48 |
| 2 | 6 | |
| 3 | 1 | |
| 4 | 27 | |
| 5 | 104 | |
| 6 | 1 | |
| 7 | A machine learning approach to determine refractive errors of the eye | 2 |
| 8 | 240 | |
| 9 | 28 | |
| 10 | 26 |
About Christian Leibig
Christian Leibig is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 10 papers that have together received 483 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), AI in cancer detection (5 papers) and Global Cancer Incidence and Screening (3 papers). The work is most often cited by research in Health Informatics (106 citations), Radiology, Nuclear Medicine and Imaging (206 citations) and Artificial Intelligence (270 citations). Christian Leibig has collaborated with scholars based in Germany, Switzerland and Austria. Frequent co-authors include Siegfried Wahl, Philipp Berens, Vaneeda Allken, Murat Seçkin Ayhan, Lale Umutlu, Katja Pinker, Günther Zeck, Thomas Wächtler, Anastasia Andreadaki and Dietmar Fischer. Their work appears in journals such as Nature Medicine, Cancer Research and Scientific Reports.
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.