David Baehrens

835 total citations
5 papers, 42 citations indexed

About

David Baehrens is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Statistics, Probability and Uncertainty. According to data from OpenAlex, David Baehrens has authored 5 papers receiving a total of 42 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 2 papers in Computational Theory and Mathematics and 2 papers in Statistics, Probability and Uncertainty. Recurrent topics in David Baehrens's work include Meta-analysis and systematic reviews (2 papers), Computational Drug Discovery Methods (2 papers) and Imbalanced Data Classification Techniques (1 paper). David Baehrens is often cited by papers focused on Meta-analysis and systematic reviews (2 papers), Computational Drug Discovery Methods (2 papers) and Imbalanced Data Classification Techniques (1 paper). David Baehrens collaborates with scholars based in Switzerland, Germany and United States. David Baehrens's co-authors include Matthias Rupp, Katja Hansen, Timon Schroeter, Klaus‐Robert Müller, A. Witzmann, Ṣẹ̀yẹ Abògúnr̀in and Michael D. Sumner and has published in prestigious journals such as Value in Health, Clinical and Translational Science and Molecular Informatics.

In The Last Decade

David Baehrens

5 papers receiving 42 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David Baehrens Switzerland	3	20	17	11	10	6	5	42
Benjamin A. Cordier United States	2	34 1.7×	12 0.7×	9 0.8×	4 0.4×	2 0.3×	2	47
Vidul Ayakulangara Panickan United States	5	20 1.0×	8 0.5×	12 1.1×	3 0.3×	3 0.5×	8	39
Laura Daza Colombia	4	6 0.3×	14 0.8×	11 1.0×	7 0.7×	2 0.3×	5	45
Jignesh Bhate Germany	3	13 0.7×	11 0.6×	19 1.7×	6 0.6×		5	34
Dmitry Lepikhin United States	2	6 0.3×	21 1.2×	18 1.6×	4 0.4×		3	30
Robert Pinsler United Kingdom	3	19 0.9×	20 1.2×	32 2.9×	31 3.1×		3	68
Youzhi Luo China	2	19 0.9×	37 2.2×	30 2.7×	38 3.8×		3	68
Maksim Kuznetsov Canada	4	9 0.5×	29 1.7×	24 2.2×	24 2.4×		8	61
M. Lucio Martínez United States	1	8 0.4×	16 0.9×	10 0.9×	3 0.3×		2	28
Takashi Yamakawa Japan	4	31 1.6×	11 0.6×	2 0.2×	5 0.5×		14	42

Countries citing papers authored by David Baehrens

Since Specialization

Citations

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

Fields of papers citing papers by David Baehrens

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Baehrens

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

All Works

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5 of 5 papers shown

1.

Baehrens, David, et al.. (2022). Machine learning approach to identify adverse events in scientific biomedical literature. Clinical and Translational Science. 15(6). 1500–1506. 2 indexed citations

2.

Witzmann, A., et al.. (2022). POSB317 Machines As a Second Reviewer in Systematic Literature Reviews. Value in Health. 25(1). S205–S206. 1 indexed citations

3.

Abògúnr̀in, Ṣẹ̀yẹ, et al.. (2020). ML1 Do Machines Perform Better THAN Humans at Systematic Review of Published Literature? a Case Study of Prostate Cancer Clinical Evidence. Value in Health. 23. S404–S404. 2 indexed citations

4.

Witzmann, A., et al.. (2020). PNS218 A Systematic Review of NON-SMALL Cell LUNG Cancer Clinical Trial Literature: Robots Versus Humans. Value in Health. 23. S677–S677. 1 indexed citations

5.

Hansen, Katja, David Baehrens, Timon Schroeter, Matthias Rupp, & Klaus‐Robert Müller. (2011). Visual Interpretation of Kernel‐Based Prediction Models. Molecular Informatics. 30(9). 817–826. 36 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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