Michaela Unger
- Health Informatics top 0.2%
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Molecular Biology
- Public Health, Environmental and Occupational Health
- Co-authors
- Jakob Nikolas KatherSophia J. WagnerGregory Patrick VeldhuizenZunamys I. CarreroNarmin Ghaffari LalehHannah Sophie MutiJan ClusmannFiona R. Kolbinger
- Topics
- Radiomics and Machine Learning in Medical Imaging (4 papers)Cancer Genomics and Diagnostics (3 papers)AI in cancer detection (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaNature ProtocolsGenome Medicine
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Michaela Unger
4 papers receiving 542 citations
Hit Papers
Peers
Comparison fields: 5 of 107
- Health Informatics 291
- Artificial Intelligence 237
- Radiology, Nuclear Medicine and Imaging 173
- Molecular Biology 48
- Public Health, Environmental and Occupational Health 37
Countries citing papers authored by Michaela Unger
This map shows the geographic impact of Michaela Unger'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 Michaela Unger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michaela Unger more than expected).
Fields of papers citing papers by Michaela Unger
This network shows the impact of papers produced by Michaela Unger. 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 Michaela Unger. The network helps show where Michaela Unger may publish in the future.
Co-authorship network of co-authors of Michaela Unger
This figure shows the co-authorship network connecting the top 25 collaborators of Michaela Unger. A scholar is included among the top collaborators of Michaela Unger 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 Michaela Unger. Michaela Unger is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 21 | |
| 2 | 0 | |
| 3 | 36 | |
| 4 | 27 | |
| 5 | The future landscape of large language models in medicinebreakdown → | 472 |
About Michaela Unger
Michaela Unger is a scholar working on Health Informatics, Cancer Research and Radiology, Nuclear Medicine and Imaging, having authored 5 papers that have together received 556 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Cancer Genomics and Diagnostics (3 papers) and AI in cancer detection (3 papers). The work is most often cited by research in Health Informatics (291 citations), Family Practice (28 citations) and Radiology, Nuclear Medicine and Imaging (173 citations). Michaela Unger has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Jakob Nikolas Kather, Sophia J. Wagner, Gregory Patrick Veldhuizen, Zunamys I. Carrero, Narmin Ghaffari Laleh, Hannah Sophie Muti, Jan Clusmann, Fiona R. Kolbinger, Chiara Maria Lavinia Löffler and Jan‐Niklas Eckardt. Their work appears in journals such as SHILAP Revista de lepidopterología, Nature Protocols and Genome Medicine.
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.