Michael Lippert

419 total citations
9 papers, 300 citations indexed

About

Michael Lippert is a scholar working on Radiology, Nuclear Medicine and Imaging, Cancer Research and Molecular Biology. According to data from OpenAlex, Michael Lippert has authored 9 papers receiving a total of 300 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Cancer Research and 3 papers in Molecular Biology. Recurrent topics in Michael Lippert's work include Radiomics and Machine Learning in Medical Imaging (4 papers), Breast Cancer Treatment Studies (3 papers) and AI in cancer detection (3 papers). Michael Lippert is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), Breast Cancer Treatment Studies (3 papers) and AI in cancer detection (3 papers). Michael Lippert collaborates with scholars based in Denmark, Sweden and United Kingdom. Michael Lippert's co-authors include Johan Hartman, Jonas Bergh, Mattias Rantalainen, Gustav Stålhammar, Stephanie Robertson, Gustaf Rosin, Lars Pedersen, Michael Grunkin, Lóránd Kis and Nicholas P. Tobin and has published in prestigious journals such as Cancer Research, Breast Cancer Research and Treatment and Modern Pathology.

In The Last Decade

Michael Lippert

9 papers receiving 298 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Lippert Denmark 7 122 109 108 101 56 9 300
Justinas Besusparis Lithuania 10 146 1.2× 114 1.0× 115 1.1× 112 1.1× 63 1.1× 29 369
Kate Lillard Japan 6 161 1.3× 145 1.3× 136 1.3× 57 0.6× 71 1.3× 7 390
Raimundas Meškauskas Lithuania 10 85 0.7× 126 1.2× 53 0.5× 107 1.1× 81 1.4× 23 370
Saba Shafi United States 10 123 1.0× 135 1.2× 126 1.2× 49 0.5× 60 1.1× 42 387
Birgid Schömig‐Markiefka Germany 7 84 0.7× 66 0.6× 87 0.8× 54 0.5× 30 0.5× 17 226
Carmen van Dooijeweert Netherlands 11 116 1.0× 131 1.2× 99 0.9× 105 1.0× 26 0.5× 29 304
David Farnell Canada 10 90 0.7× 56 0.5× 69 0.6× 44 0.4× 62 1.1× 22 383
Hubert G. Bartels United States 13 128 1.0× 105 1.0× 78 0.7× 51 0.5× 99 1.8× 52 459
Aurélie Fernandez Germany 5 151 1.2× 119 1.1× 181 1.7× 64 0.6× 54 1.0× 8 353
Anne Grabenstetter United States 9 93 0.8× 81 0.7× 76 0.7× 97 1.0× 23 0.4× 23 257

Countries citing papers authored by Michael Lippert

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Michael Lippert

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Lippert. A scholar is included among the top collaborators of Michael Lippert 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 Michael Lippert. Michael Lippert is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Robertson, Stephanie, Balázs Ács, Michael Lippert, & Johan Hartman. (2020). Prognostic potential of automated Ki67 evaluation in breast cancer: different hot spot definitions versus true global score. Breast Cancer Research and Treatment. 183(1). 161–175. 31 indexed citations
2.
Klarskov, Louise Laurberg, Michael Lippert, Guy Wayne Novotny, et al.. (2018). Digital image analysis of pan-cytokeratin stained tumor slides for evaluation of tumor budding in pT1/pT2 colorectal cancer: Results of a feasibility study. Pathology - Research and Practice. 214(9). 1273–1281. 15 indexed citations
3.
Lelkaitis, Giedrius, et al.. (2017). Virtual Double Staining: A Digital Approach to Immunohistochemical Quantification of Estrogen Receptor Protein in Breast Carcinoma Specimens. Applied immunohistochemistry & molecular morphology. 26(9). 620–626. 22 indexed citations
4.
Stålhammar, Gustav, Stephanie Robertson, Michael Lippert, et al.. (2017). Digital image analysis of Ki67 in hot spots is superior to both manual Ki67 and mitotic counts in breast cancer. Histopathology. 72(6). 974–989. 71 indexed citations
5.
Conradsen, Knut, et al.. (2017). Quantitative tumor heterogeneity assessment on a nuclear population basis. Cytometry Part A. 91(6). 574–584. 4 indexed citations
6.
Stålhammar, Gustav, Michael Lippert, Nicholas P. Tobin, et al.. (2016). Digital image analysis outperforms manual biomarker assessment in breast cancer. Modern Pathology. 29(4). 318–329. 130 indexed citations
7.
Stålhammar, Gustav, Gustaf Rosin, Lóránd Kis, et al.. (2016). Abstract P1-01-06: Digital image analysis outperforms manual scoring for breast cancer subclassification and prognostication. Cancer Research. 76(4_Supplement). P1–1. 1 indexed citations
8.
Strand, Robin, et al.. (2014). A histopathological tool for quantification of biomarkers with sub-cellular resolution. Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization. 3(1). 25–46. 6 indexed citations
9.
Almstrup, Kristian, Michael Lippert, Jens Høiriis Nielsen, et al.. (2011). Screening of subfertile men for testicular carcinoma in situ by an automated image analysis‐based cytological test of the ejaculate. International Journal of Andrology. 34(4pt2). e21–30; discussion e30. 20 indexed citations

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.

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