Michael Lippert
Impact in
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- Breast Cancer Treatment Studies
- Cancer Genomics and Diagnostics
- Biophysics top 10%
- Cell Image Analysis Techniques
Papers in
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- Radiomics and Machine Learning in Medical Imaging 4
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- Breast Cancer Treatment Studies 3
- Cancer Genomics and Diagnostics 2
- Co-authors
- Johan Hartman (3 shared papers)Jonas Bergh (3 shared papers)Mattias Rantalainen (2 shared papers)Gustav Stålhammar (3 shared papers)Stephanie Robertson (2 shared papers)Lóránd Kis (2 shared papers)Gustaf Rosin (2 shared papers)Lars Pedersen (1 shared paper)
- Journals
- Applied immunohistochemistry & molecular morphology (1 paper)Modern Pathology (1 paper)Histopathology (1 paper)Breast Cancer Research and Treatment (1 paper)International Journal of Andrology (1 paper)
- Partner nations
- DenmarkSwedenUnited Kingdom
In The Last Decade
Michael Lippert
9 papers receiving 298 citations
Peers
Comparison fields: 5 of 55
- Cancer Research 101
- Biophysics 34
- Health Informatics 7
- Radiology, Nuclear Medicine and Imaging 108
- Oncology 109
Countries citing papers authored by Michael Lippert
This map shows the geographic impact of Michael Lippert'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 Michael Lippert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Lippert more than expected).
Fields of papers citing papers by Michael Lippert
This network shows the impact of papers produced by Michael Lippert. 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 Michael Lippert. The network helps show where Michael Lippert may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Lippert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 130 | |
| 2 | 2017 | 71 | |
| 3 | 2020 | 31 | |
| 4 | 2017 | 22 | |
| 5 | 2011 | 20 | |
| 6 | 2018 | 15 | |
| 7 | 2014 | 6 | |
| 8 | 2017 | 4 | |
| 9 | 2016 | 1 |
About Michael Lippert
Michael Lippert is a scholar working on Radiology, Nuclear Medicine and Imaging, Cancer Research, Molecular Biology, Artificial Intelligence and Pathology and Forensic Medicine, having authored 9 papers that have together received 300 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Breast Cancer Treatment Studies (3 papers), AI in cancer detection (3 papers), Cancer Genomics and Diagnostics (2 papers), Cell Image Analysis Techniques (2 papers), Gene expression and cancer classification (2 papers), Breast Lesions and Carcinomas (2 papers) and Colorectal Cancer Surgical Treatments (1 paper). The work is most often cited by research in Cancer Research (101 citations), Biophysics (34 citations), Health Informatics (7 citations), Radiology, Nuclear Medicine and Imaging (108 citations) and Oncology (109 citations). Michael Lippert has collaborated with scholars based in Denmark, Sweden and United Kingdom. Frequent co-authors include Johan Hartman, Jonas Bergh, Mattias Rantalainen, Gustav Stålhammar, Stephanie Robertson, Lóránd Kis, Gustaf Rosin, Lars Pedersen, Nicholas P. Tobin and Michael Grunkin. Their work appears in journals such as Applied immunohistochemistry & molecular morphology, Modern Pathology, Histopathology, Breast Cancer Research and Treatment and International Journal of Andrology.
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.