Stephanie Robertson

2.5k total citations
28 papers, 1.1k citations indexed

About

Stephanie Robertson is a scholar working on Cancer Research, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Stephanie Robertson has authored 28 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cancer Research, 12 papers in Oncology and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Stephanie Robertson's work include Breast Cancer Treatment Studies (10 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and AI in cancer detection (7 papers). Stephanie Robertson is often cited by papers focused on Breast Cancer Treatment Studies (10 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and AI in cancer detection (7 papers). Stephanie Robertson collaborates with scholars based in Sweden, United States and Singapore. Stephanie Robertson's co-authors include Johan Hartman, Hossein Azizpour, Kevin Smith, Mattias Rantalainen, Balázs Ács, Lori S. Friedman, Carol Prives, Geoffrey M. Duyk, William W. Fisher and Michael Ollmann and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Clinical Oncology.

In The Last Decade

Stephanie Robertson

25 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephanie Robertson Sweden 14 430 408 298 296 195 28 1.1k
Hanne A. Askautrud Norway 12 317 0.7× 563 1.4× 246 0.8× 346 1.2× 227 1.2× 22 1.3k
Robin Edwards United States 12 493 1.1× 492 1.2× 195 0.7× 205 0.7× 219 1.1× 25 1.1k
Vilppu J. Tuominen Finland 12 295 0.7× 285 0.7× 189 0.6× 154 0.5× 164 0.8× 13 816
Bing Ren United States 12 833 1.9× 709 1.7× 178 0.6× 167 0.6× 201 1.0× 26 1.5k
Andreas Heindl United Kingdom 12 290 0.7× 246 0.6× 171 0.6× 202 0.7× 173 0.9× 19 776
Douglas Bowman United States 7 307 0.7× 281 0.7× 337 1.1× 214 0.7× 95 0.5× 8 882
Sheida Nabavi United States 17 459 1.1× 162 0.4× 424 1.4× 356 1.2× 208 1.1× 50 1.1k
Maeve Mullooly Ireland 17 343 0.8× 614 1.5× 213 0.7× 291 1.0× 264 1.4× 49 1.2k
Alexander Brobeil Germany 16 310 0.7× 175 0.4× 158 0.5× 169 0.6× 111 0.6× 64 722
Ute Pohl United Kingdom 16 808 1.9× 174 0.4× 175 0.6× 114 0.4× 288 1.5× 35 1.5k

Countries citing papers authored by Stephanie Robertson

Since Specialization
Citations

This map shows the geographic impact of Stephanie Robertson'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 Stephanie Robertson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephanie Robertson more than expected).

Fields of papers citing papers by Stephanie Robertson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephanie Robertson. 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 Stephanie Robertson. The network helps show where Stephanie Robertson may publish in the future.

Co-authorship network of co-authors of Stephanie Robertson

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

All Works

20 of 20 papers shown
1.
Sifakis, Emmanouil G., et al.. (2025). Transcriptomic profiles of endocrine-resistant breast cancer. BMC Cancer. 25(1). 1556–1556.
2.
Sifakis, Emmanouil G., Emelié Karlsson, Xinsong Chen, et al.. (2024). Prognostic impact of HER2 biomarker levels in trastuzumab-treated early HER2-positive breast cancer. Breast Cancer Research. 26(1). 24–24. 2 indexed citations
3.
Wang, Yinxi, et al.. (2024). Validation of an AI-based solution for breast cancer risk stratification using routine digital histopathology images. Breast Cancer Research. 26(1). 123–123. 5 indexed citations
4.
Robertson, Stephanie, et al.. (2024). PIK3CA mutations in endocrine-resistant breast cancer. Scientific Reports. 14(1). 12542–12542. 4 indexed citations
5.
Wang, Yinxi, Wenwen Sun, Emelié Karlsson, et al.. (2024). Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay. Breast Cancer Research and Treatment. 206(1). 163–175. 4 indexed citations
6.
Solorzano, Leslie, Stephanie Robertson, Balázs Ács, Johan Hartman, & Mattias Rantalainen. (2024). Ensemble-based deep learning improves detection of invasive breast cancer in routine histopathology images. Heliyon. 10(12). e32892–e32892. 4 indexed citations
7.
Robertson, Stephanie, et al.. (2024). Abstract PO3-16-04: Distribution of intrinsic subtypes in endocrine-resistant and endocrine-sensitive breast cancer. Cancer Research. 84(9_Supplement). PO3–16. 1 indexed citations
8.
Wang, Yinxi, et al.. (2024). Deep learning-based risk stratification of preoperative breast biopsies using digital whole slide images. Breast Cancer Research. 26(1). 90–90. 4 indexed citations
9.
Chen, Xinsong, Emmanouil G. Sifakis, Stephanie Robertson, et al.. (2022). 1668P Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction. Annals of Oncology. 33. S1306–S1306. 1 indexed citations
10.
Wang, Yinxi, Balázs Ács, Stephanie Robertson, et al.. (2021). Improved breast cancer histological grading using deep learning. Annals of Oncology. 33(1). 89–98. 125 indexed citations
11.
Sun, Wenwen, et al.. (2021). Independent Clinical Validation of the Automated Ki67 Scoring Guideline from the International Ki67 in Breast Cancer Working Group. Biomolecules. 11(11). 1612–1612. 17 indexed citations
12.
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
13.
Robertson, Stephanie, et al.. (2019). Re-testing of predictive biomarkers on surgical breast cancer specimens is clinically relevant. Breast Cancer Research and Treatment. 174(3). 795–805. 35 indexed citations
14.
Robertson, Stephanie, Gustav Stålhammar, Mattias Rantalainen, et al.. (2018). Prognostic value of Ki67 analysed by cytology or histology in primary breast cancer. Journal of Clinical Pathology. 71(9). 787–794. 21 indexed citations
15.
Robertson, Stephanie, Hossein Azizpour, Kevin Smith, & Johan Hartman. (2017). Digital image analysis in breast pathology—from image processing techniques to artificial intelligence. Translational research. 194. 19–35. 204 indexed citations
16.
Robertson, Stephanie, et al.. (2017). Waiting times for cancer patients in Sweden: A nationwide population-based study. Scandinavian Journal of Public Health. 45(3). 230–237. 15 indexed citations
17.
18.
Wilke, Lee G., Gloria Broadwater, Elizabeth B. Owens, et al.. (2009). Breast self-examination: defining a cohort still in need. The American Journal of Surgery. 198(4). 575–579. 30 indexed citations
19.
Groot, John de, Michael D. Prados, Stephanie Robertson, et al.. (2009). A phase II study of XL184 in patients (pts) with progressive glioblastoma multiforme (GBM) in first or second relapse. Journal of Clinical Oncology. 27(15_suppl). 2047–2047. 34 indexed citations
20.
Ollmann, Michael, Lynn Young, Charles J. Di Como, et al.. (2000). Drosophila p53 Is a Structural and Functional Homolog of the Tumor Suppressor p53. Cell. 101(1). 91–101. 336 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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