Katja Siegmann-Luz
- Radiology, Nuclear Medicine and Imaging top 10%
- Pathology and Forensic Medicine
- Cancer Research
- Obstetrics and Gynecology top 10%
- Artificial Intelligence
- Co-authors
- Heike PreibschAnnette StaeblerBeate WietekMarkus HahnClaus D. ClaussenSara Y. BruckerKatharina RallKonstantin Nikolaou
- Topics
- MRI in cancer diagnosis (9 papers)Radiomics and Machine Learning in Medical Imaging (8 papers)Breast Cancer Treatment Studies (7 papers)
- Partner nations
- GermanyAustriaSwitzerland
In The Last Decade
Katja Siegmann-Luz
21 papers receiving 301 citations
Hit Papers
Peers
Comparison fields: 5 of 39
- Radiology, Nuclear Medicine and Imaging 164
- Pathology and Forensic Medicine 95
- Cancer Research 78
- Obstetrics and Gynecology 50
- Artificial Intelligence 46
Countries citing papers authored by Katja Siegmann-Luz
This map shows the geographic impact of Katja Siegmann-Luz'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 Katja Siegmann-Luz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Katja Siegmann-Luz more than expected).
Fields of papers citing papers by Katja Siegmann-Luz
This network shows the impact of papers produced by Katja Siegmann-Luz. 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 Katja Siegmann-Luz. The network helps show where Katja Siegmann-Luz may publish in the future.
Co-authorship network of co-authors of Katja Siegmann-Luz
This figure shows the co-authorship network connecting the top 25 collaborators of Katja Siegmann-Luz. A scholar is included among the top collaborators of Katja Siegmann-Luz 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 Katja Siegmann-Luz. Katja Siegmann-Luz 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 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 8 | |
| 8 | 13 | |
| 9 | 6 | |
| 10 | 8 | |
| 11 | 61 | |
| 12 | 4 | |
| 13 | 17 | |
| 14 | 9 | |
| 15 | 49 | |
| 16 | 1 | |
| 17 | 2 | |
| 18 | 7 | |
| 19 | 33 | |
| 20 | 9 |
About Katja Siegmann-Luz
Katja Siegmann-Luz is a scholar working on Radiology, Nuclear Medicine and Imaging, Cancer Research and Pathology and Forensic Medicine, having authored 22 papers that have together received 307 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (9 papers), Radiomics and Machine Learning in Medical Imaging (8 papers) and Breast Cancer Treatment Studies (7 papers). The work is most often cited by research in Health Informatics (16 citations), Radiology, Nuclear Medicine and Imaging (164 citations) and Obstetrics and Gynecology (50 citations). Katja Siegmann-Luz has collaborated with scholars based in Germany, Austria and Switzerland. Frequent co-authors include Heike Preibsch, Annette Staebler, Beate Wietek, Markus Hahn, Claus D. Claussen, Sara Y. Brucker, Katharina Rall, Konstantin Nikolaou, Bernhard Krämer and Benjamin Wiesinger. Their work appears in journals such as Nature Medicine, European Radiology and European Journal of Radiology.
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.