Christian Pohlkamp

408 total citations
18 papers, 151 citations indexed

About

Christian Pohlkamp is a scholar working on Hematology, Genetics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Christian Pohlkamp has authored 18 papers receiving a total of 151 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Hematology, 7 papers in Genetics and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Christian Pohlkamp's work include Acute Myeloid Leukemia Research (7 papers), Digital Imaging for Blood Diseases (7 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers). Christian Pohlkamp is often cited by papers focused on Acute Myeloid Leukemia Research (7 papers), Digital Imaging for Blood Diseases (7 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers). Christian Pohlkamp collaborates with scholars based in Germany, United States and Australia. Christian Pohlkamp's co-authors include Torsten Haferlach, Wolfgang Kern, Claudia Haferlach, Manja Meggendorfer, Constance Baer, Niroshan Nadarajah, Wencke Walter, Stephan Hütter, Sandra Huber and Gregor Hoermann and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and Leukemia.

In The Last Decade

Christian Pohlkamp

15 papers receiving 147 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christian Pohlkamp Germany 7 69 42 33 32 29 18 151
Alexander Höllein Germany 7 124 1.8× 47 1.1× 21 0.6× 91 2.8× 61 2.1× 14 209
Carolien Duetz Netherlands 6 72 1.0× 31 0.7× 12 0.4× 43 1.3× 8 0.3× 15 133
José Ángel Díaz Arias Spain 9 67 1.0× 30 0.7× 9 0.3× 99 3.1× 38 1.3× 20 184
Christian Brieghel Denmark 9 36 0.5× 168 4.0× 10 0.3× 20 0.6× 15 0.5× 32 260
David C. Shyr United States 6 36 0.5× 17 0.4× 8 0.2× 34 1.1× 8 0.3× 24 102
Nikolaos Sousos United Kingdom 7 162 2.3× 125 3.0× 28 0.8× 192 6.0× 82 2.8× 15 362
Stefanie Warnat‐Herresthal Germany 4 19 0.3× 7 0.2× 23 0.7× 80 2.5× 17 0.6× 6 231
Georgiana Grigore Spain 6 44 0.6× 24 0.6× 7 0.2× 50 1.6× 15 0.5× 12 131
Chi‐Yuan Yao Taiwan 9 129 1.9× 59 1.4× 17 0.5× 119 3.7× 69 2.4× 38 253
Celina Benavente Spain 8 160 2.3× 102 2.4× 19 0.6× 35 1.1× 7 0.2× 21 199

Countries citing papers authored by Christian Pohlkamp

Since Specialization
Citations

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

Fields of papers citing papers by Christian Pohlkamp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christian Pohlkamp

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

All Works

18 of 18 papers shown
1.
Eckardt, Jan‐Niklas, Susann Winter, Katja Sockel, et al.. (2025). Image-based explainable artificial intelligence accurately identifies myelodysplastic neoplasms beyond conventional signs of dysplasia. npj Precision Oncology. 10(1). 26–26.
2.
Lenk, Miriam, Wolfgang Kern, Claudia Haferlach, et al.. (2025). Sequential occurrence of BCR::ABL1-negative MPN and CML and vice versa: results from a real world cohort. International Journal of Hematology. 122(6). 835–842.
3.
Haferlach, Torsten, Jan‐Niklas Eckardt, Wencke Walter, et al.. (2025). AML diagnostics in the 21st century: Use of AI. Seminars in Hematology. 62(3). 226–234. 2 indexed citations
4.
Huber, Sandra, Torsten Haferlach, Stephan Hütter, et al.. (2024). Parallel genomic analysis from paired bone marrow and peripheral blood samples of 200 cytopenic patients. Leukemia. 38(7). 1626–1629. 3 indexed citations
5.
Huber, Sandra, Constance Baer, Stephan Hütter, et al.. (2024). Genomic landscape of CCUS compared to MDS and its implications on risk prediction. Leukemia. 38(7). 1634–1637. 4 indexed citations
6.
Maierhofer, Anna, Nikita Mehta, Ryan A. Chisholm, et al.. (2023). The clinical and genomic landscape of patients with DDX41 variants identified during diagnostic sequencing. Blood Advances. 7(23). 7346–7357. 9 indexed citations
7.
Huber, Sandra, Constance Baer, Stephan Hütter, et al.. (2023). AML classification in the year 2023: How to avoid a Babylonian confusion of languages. Leukemia. 37(7). 1413–1420. 32 indexed citations
8.
Matek, Christian, et al.. (2023). Explainable AI identifies diagnostic cells of genetic AML subtypes. SHILAP Revista de lepidopterología. 2(3). e0000187–e0000187. 13 indexed citations
9.
Walter, Wencke, Christian Pohlkamp, Manja Meggendorfer, et al.. (2022). Artificial intelligence in hematological diagnostics: Game changer or gadget?. Blood Reviews. 58. 101019–101019. 34 indexed citations
10.
Huber, Sandra, Constance Baer, Stephan Hütter, et al.. (2022). AML and MDS Classification According to Who 2022 and International Consensus Classification: Do We Invent a Babylonian Confusion of Languages?. Blood. 140(Supplement 1). 555–556. 5 indexed citations
11.
Haferlach, Torsten, Niroshan Nadarajah, Claudia Haferlach, Wolfgang Kern, & Christian Pohlkamp. (2022). Machine Learning Algorithm Correctly Identifies 95% of Cells in Differential Count of Blood Smears: A Prospective Study on >29,000 Cases and >17 Million Single Cells. Blood. 140(Supplement 1). 1909–1910. 1 indexed citations
12.
Pohlkamp, Christian, Niroshan Nadarajah, Piyush Srivastava, et al.. (2022). A Fully Automated Digital Workflow for Assessment of Bone Marrow Cytomorphology Based on Single Cell Detection and Classification with AI. Blood. 140(Supplement 1). 10725–10726. 3 indexed citations
13.
Hoermann, Gregor, Manja Meggendorfer, Constance Baer, et al.. (2021). Whole Genome Sequencing Identifies Non-KIT Mutations and Cytogenetic Aberrations in Systemic Mastocytosis but Has Limited Sensitivity for Detection of KIT D816V. Blood. 138(Supplement 1). 1495–1495.
14.
Haferlach, Torsten, Christian Pohlkamp, Thomas Lörch, et al.. (2021). Automated Peripheral Blood Cell Differentiation Using Artificial Intelligence - a Study with More Than 10,000 Routine Samples in a Specialized Leukemia Laboratory. Blood. 138(Supplement 1). 103–103. 9 indexed citations
15.
Welt, Anja, Simon Bogner, Marina Arendt, et al.. (2020). Improved survival in metastatic breast cancer: results from a 20-year study involving 1033 women treated at a single comprehensive cancer center. Journal of Cancer Research and Clinical Oncology. 146(6). 1559–1566. 15 indexed citations
16.
Maierhofer, Anna, Constance Baer, Christian Pohlkamp, et al.. (2020). Putative Germline Variants in the Predisposition Genes DDX41, ETV6 and GATA2 investigated in 1,228 Patients with Sporadic AML or MDS. Blood. 136(Supplement 1). 17–18. 1 indexed citations
17.
Pohlkamp, Christian, Niroshan Nadarajah, Thomas Lörch, et al.. (2020). Machine Learning (ML) Can Successfully Support Microscopic Differential Counts of Peripheral Blood Smears in a High Throughput Hematology Laboratory. Blood. 136(Supplement 1). 45–46. 6 indexed citations
18.
Baer, Constance, Christian Pohlkamp, Claudia Haferlach, Wolfgang Kern, & Torsten Haferlach. (2018). Molecular patterns in cytopenia patients with or without evidence of myeloid neoplasm—a comparison of 756 cases. Leukemia. 32(10). 2295–2298. 14 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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2026