Christoph M. Friedrich

5.5k total citations
118 papers, 1.5k citations indexed

About

Christoph M. Friedrich is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Christoph M. Friedrich has authored 118 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Artificial Intelligence, 31 papers in Molecular Biology and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Christoph M. Friedrich's work include Biomedical Text Mining and Ontologies (27 papers), Topic Modeling (17 papers) and Machine Learning in Healthcare (11 papers). Christoph M. Friedrich is often cited by papers focused on Biomedical Text Mining and Ontologies (27 papers), Topic Modeling (17 papers) and Machine Learning in Healthcare (11 papers). Christoph M. Friedrich collaborates with scholars based in Germany, United States and Switzerland. Christoph M. Friedrich's co-authors include Martin Hofmann‐Apitius, Roman Klinger, Felix Nensa, Juliane Fluck, Sven Koitka, Obioma Pelka, Raphael Brüngel, Meike Nauta, Christin Seifert and Nicole C. Krämer and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

Christoph M. Friedrich

102 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christoph M. Friedrich Germany 21 462 346 241 168 138 118 1.5k
Shyam Visweswaran United States 23 721 1.6× 499 1.4× 89 0.4× 200 1.2× 79 0.6× 129 1.9k
Corey Arnold United States 24 657 1.4× 162 0.5× 241 1.0× 430 2.6× 166 1.2× 105 1.7k
Julian M.W. Quinn Australia 34 477 1.0× 1.2k 3.3× 87 0.4× 360 2.1× 91 0.7× 71 3.1k
Pierangelo Veltri Italy 23 629 1.4× 581 1.7× 252 1.0× 205 1.2× 117 0.8× 237 2.2k
Qingyu Chen China 27 895 1.9× 835 2.4× 124 0.5× 608 3.6× 162 1.2× 134 3.0k
Javier Andreu-Pérez United Kingdom 18 885 1.9× 179 0.5× 359 1.5× 482 2.9× 458 3.3× 77 2.9k
Matthew Chin Heng Chua Singapore 21 289 0.6× 198 0.6× 224 0.9× 207 1.2× 158 1.1× 62 1.2k
Themis P. Exarchos Greece 19 1.1k 2.4× 719 2.1× 161 0.7× 654 3.9× 279 2.0× 98 3.2k
Abubakar Abid United States 12 808 1.7× 569 1.6× 156 0.6× 321 1.9× 130 0.9× 22 2.0k
Marcus A. Badgeley United States 16 613 1.3× 225 0.7× 104 0.4× 708 4.2× 230 1.7× 21 2.0k

Countries citing papers authored by Christoph M. Friedrich

Since Specialization
Citations

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

Fields of papers citing papers by Christoph M. Friedrich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christoph M. Friedrich. 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 Christoph M. Friedrich. The network helps show where Christoph M. Friedrich may publish in the future.

Co-authorship network of co-authors of Christoph M. Friedrich

This figure shows the co-authorship network connecting the top 25 collaborators of Christoph M. Friedrich. A scholar is included among the top collaborators of Christoph M. Friedrich 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 Christoph M. Friedrich. Christoph M. Friedrich 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.
Lodde, Georg, Elisabeth Livingstone, Carsten Weishaupt, et al.. (2025). Fully volumetric body composition analysis for prognostic overall survival stratification in melanoma patients. Journal of Translational Medicine. 23(1). 532–532.
2.
Haubold, Johannes, Benedikt M. Schaarschmidt, Marcel Opitz, et al.. (2025). Moving Beyond CT Body Composition Analysis. Investigative Radiology. 60(8). 552–559. 1 indexed citations
3.
Schäfer, Henning, Héctor Allende‐Cid, Giulia Baldini, et al.. (2025). From BERT to generative AI - Comparing encoder-only vs. large language models in a cohort of lung cancer patients for named entity recognition in unstructured medical reports. Computers in Biology and Medicine. 195. 110665–110665. 1 indexed citations
4.
Pelka, Obioma, et al.. (2025). Using a Diverse Test Suite to Assess Large Language Models on Fast Health Care Interoperability Resources Knowledge: Comparative Analysis. Journal of Medical Internet Research. 27. e73540–e73540.
5.
Grossetti, G., et al.. (2025). Acoustic Event Detection in Vehicles: A Multi-Label Classification Approach. Sensors. 25(8). 2591–2591.
6.
Marini, Niccolò, Simona Vatrano, Irıs D. Nagtegaal, et al.. (2024). Automated classification of celiac disease in histopathological images: a multi-scale approach. Universitätsbibliographie, Universität Duisburg-Essen. 7. 86–86.
7.
8.
Brüngel, Raphael, Johannes Rückert, Philipp Müller, et al.. (2023). NanoDefiner Framework and e-Tool Revisited According to the European Commission’s Nanomaterial Definition 2022/C 229/01. Nanomaterials. 13(6). 990–990. 9 indexed citations
9.
Pelka, Obioma, Christoph M. Friedrich, Alba García Seco de Herrera, & Henning Müller. (2020). Overview of the ImageCLEFmed 2020 Concept Prediction Task: Medical Image Understanding.. Open Access at Essex (University of Essex). 5 indexed citations
10.
Schatlo, Bawarjan, Oliver Gautschi, Christoph M. Friedrich, et al.. (2019). Association of single and multiple aneurysms with tobacco abuse: an @neurIST risk analysis. Neurosurgical FOCUS. 47(1). E9–E9. 4 indexed citations
11.
Pelka, Obioma, Christoph M. Friedrich, Alba García Seco de Herrera, & Henning Müller. (2019). Overview of the ImageCLEFmed 2019 concept detection task. ArODES (HES-SO (https://www.hes-so.ch/)). 5 indexed citations
12.
Wyborn, Lesley, Christoph M. Friedrich, Tim Rawling, et al.. (2018). Building a multipurpose Geoscience Virtual Research Environment to cater for multiple use cases, a range of scales and diverse skill sets.. AGU Fall Meeting Abstracts. 2018. 1 indexed citations
13.
Koitka, Sven, et al.. (2018). Word Embeddings and Linguistic Metadata at the CLEF 2018 Tasks for Early Detection of Depression and Anorexia.. CLEF (Working Notes). 22 indexed citations
14.
Rex, D, et al.. (2017). Improving Model Performance for Plant Image Classification With Filtered Noisy Images.. CLEF (Working Notes). 2 indexed citations
15.
Pelka, Obioma & Christoph M. Friedrich. (2017). Keyword Generation for Biomedical Image Retrieval with Recurrent Neural Networks.. CLEF (Working Notes). 4 indexed citations
16.
Koitka, Sven & Christoph M. Friedrich. (2016). Traditional Feature Engineering and Deep Learning Approaches at Medical Classification Task of ImageCLEF 2016.. CLEF (Working Notes). 304–317. 23 indexed citations
17.
Pelka, Obioma & Christoph M. Friedrich. (2015). FHDO Biomedical Computer Science Group at Medical Classification Task of ImageCLEF 2015.. CLEF (Working Notes). 18 indexed citations
18.
Friedrich, Christoph M., Christian Ebeling, & David Manset. (2010). Cross-Project Uptake of Biomedical Text Mining Results for Candidate Gene Searches.. ERCIM news/ERCIM news online edition. 2010. 45–46. 1 indexed citations
19.
Gurulingappa, Harsha, B. G. Müller, Roman Klinger, et al.. (2010). Prior Art Search in Chemistry Patents Based On Semantic Concepts and Co-Citation Analysis.. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 6 indexed citations
20.
Klinger, Roman & Christoph M. Friedrich. (2009). User's Choice of Precision and Recall in Named Entity Recognition. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 192–196. 4 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Shyam Visweswaran Breakdown of academic impact, for papers by Corey Arnold Breakdown of academic impact, for papers by Julian M.W. Quinn Breakdown of academic impact, for papers by Pierangelo Veltri Breakdown of academic impact, for papers by Qingyu Chen Breakdown of academic impact, for papers by Javier Andreu-Pérez Breakdown of academic impact, for papers by Matthew Chin Heng Chua Breakdown of academic impact, for papers by Themis P. Exarchos Breakdown of academic impact, for papers by Abubakar Abid Breakdown of academic impact, for papers by Marcus A. Badgeley
Rankless by CCL
2026