Didem Çifçi

544 total citations
10 papers, 167 citations indexed

About

Didem Çifçi is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging and Cancer Research. According to data from OpenAlex, Didem Çifçi has authored 10 papers receiving a total of 167 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Oncology, 5 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Cancer Research. Recurrent topics in Didem Çifçi's work include Colorectal Cancer Screening and Detection (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Cancer Genomics and Diagnostics (4 papers). Didem Çifçi is often cited by papers focused on Colorectal Cancer Screening and Detection (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Cancer Genomics and Diagnostics (4 papers). Didem Çifçi collaborates with scholars based in Germany, United Kingdom and United States. Didem Çifçi's co-authors include Jakob Nikolas Kather, Sebastian Foersch, Gregory Patrick Veldhuizen, Marko van Treeck, Alexander T. Pearson, Jan Niehues, Tobias Paul Seraphin, Oliver Lester Saldanha, Katherine Hewitt and Chiara Maria Lavinia Loeffler and has published in prestigious journals such as Scientific Reports, The Journal of Pathology and Journal of Clinical Pathology.

In The Last Decade

Didem Çifçi

8 papers receiving 164 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Didem Çifçi Germany 5 113 103 45 37 29 10 167
Omar S. M. El Nahhas Germany 7 75 0.7× 92 0.9× 34 0.8× 31 0.8× 25 0.9× 11 177
Roman D. Buelow Germany 7 85 0.8× 109 1.1× 47 1.0× 28 0.8× 26 0.9× 8 192
Sami Tabbarah Canada 6 142 1.3× 100 1.0× 25 0.6× 44 1.2× 22 0.8× 9 190
Paula Toro United States 8 125 1.1× 92 0.9× 58 1.3× 37 1.0× 21 0.7× 27 239
Andrew Lagree Canada 11 192 1.7× 151 1.5× 52 1.2× 61 1.6× 25 0.9× 15 295
Oliver Lester Saldanha Germany 6 166 1.5× 100 1.0× 92 2.0× 40 1.1× 14 0.5× 11 227
Igor Odintsov United States 5 98 0.9× 143 1.4× 37 0.8× 26 0.7× 28 1.0× 15 260
Birgid Schömig‐Markiefka Germany 7 87 0.8× 84 0.8× 66 1.5× 54 1.5× 17 0.6× 17 226
Asmaa Ibrahim Egypt 9 139 1.2× 156 1.5× 79 1.8× 84 2.3× 30 1.0× 22 270
Ayesha Azam United Kingdom 4 118 1.0× 144 1.4× 86 1.9× 42 1.1× 20 0.7× 7 236

Countries citing papers authored by Didem Çifçi

Since Specialization
Citations

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

Fields of papers citing papers by Didem Çifçi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Didem Çifçi

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

All Works

10 of 10 papers shown
1.
Çifçi, Didem, Gregory Patrick Veldhuizen, Wan-Jung Tsai, et al.. (2025). Deep learning predicts microsatellite instability status in colorectal carcinoma in an ethnically heterogeneous population in South Africa. Journal of Clinical Pathology. 79(1). 50–56.
2.
Veldhuizen, Gregory Patrick, Didem Çifçi, Marko van Treeck, et al.. (2025). Deep learning can predict cardiovascular events from liver imaging. JHEP Reports. 7(8). 101427–101427.
3.
Çifçi, Didem, Erwin Tomasich, Maximilian J. Mair, et al.. (2025). Density and entropy of immune cells within the tumor microenvironment of primary tumors and matched brain metastases. Acta Neuropathologica Communications. 13(1). 34–34. 1 indexed citations
4.
Loeffler, Chiara Maria Lavinia, Omar S. M. El Nahhas, Zunamys I. Carrero, et al.. (2024). Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types. BMC Biology. 22(1). 225–225. 4 indexed citations
5.
Veldhuizen, Gregory Patrick, Christoph Röcken, Hans‐Michael Behrens, et al.. (2023). Deep learning-based subtyping of gastric cancer histology predicts clinical outcome: a multi-institutional retrospective study. Gastric Cancer. 26(5). 708–720. 13 indexed citations
6.
Saldanha, Oliver Lester, Chiara Maria Lavinia Loeffler, Jan Niehues, et al.. (2023). Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology. npj Precision Oncology. 7(1). 35–35. 41 indexed citations
7.
Niehues, Jan, Marko van Treeck, Chiara Maria Lavinia Loeffler, et al.. (2023). Prediction models for hormone receptor status in female breast cancer do not extend to males: further evidence of sex-based disparity in breast cancer. npj Breast Cancer. 9(1). 91–91. 3 indexed citations
8.
Çifçi, Didem, Gregory Patrick Veldhuizen, Sebastian Foersch, & Jakob Nikolas Kather. (2023). AI in Computational Pathology of Cancer: Improving Diagnostic Workflows and Clinical Outcomes?. 7(1). 57–71. 17 indexed citations
9.
Buendgens, Lukas, Didem Çifçi, Narmin Ghaffari Laleh, et al.. (2022). Weakly supervised end-to-end artificial intelligence in gastrointestinal endoscopy. Scientific Reports. 12(1). 4829–4829. 7 indexed citations
10.
Çifçi, Didem, Sebastian Foersch, & Jakob Nikolas Kather. (2022). Artificial intelligence to identify genetic alterations in conventional histopathology. The Journal of Pathology. 257(4). 430–444. 81 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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