Anika Buchholz
- Physiology top 10%
- Statistics and Probability top 2%
- Endocrine and Autonomic Systems top 5%
- Pulmonary and Respiratory Medicine
- Cardiology and Cardiovascular Medicine
- Co-authors
- Martin SchumacherWilli SauerbreiJan BeyersmannAurélien LatoucheKarl WegscheiderHenrik FoxDieter HorstkotteBirgit Wellmann
- Topics
- Statistical Methods and Inference (7 papers)Health Systems, Economic Evaluations, Quality of Life (6 papers)Patient-Provider Communication in Healthcare (4 papers)
- Journals
- PLoS ONEThe Plant CellStroke
- Partner nations
- GermanyFranceUnited Kingdom
In The Last Decade
Anika Buchholz
25 papers receiving 742 citations
Peers
Comparison fields: 5 of 118
- Physiology 223
- Statistics and Probability 168
- Endocrine and Autonomic Systems 160
- Pulmonary and Respiratory Medicine 138
- Cardiology and Cardiovascular Medicine 105
Countries citing papers authored by Anika Buchholz
This map shows the geographic impact of Anika Buchholz'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 Anika Buchholz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anika Buchholz more than expected).
Fields of papers citing papers by Anika Buchholz
This network shows the impact of papers produced by Anika Buchholz. 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 Anika Buchholz. The network helps show where Anika Buchholz may publish in the future.
Co-authorship network of co-authors of Anika Buchholz
This figure shows the co-authorship network connecting the top 25 collaborators of Anika Buchholz. A scholar is included among the top collaborators of Anika Buchholz 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 Anika Buchholz. Anika Buchholz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 0 | |
| 4 | 8 | |
| 5 | 25 | |
| 6 | 17 | |
| 7 | 23 | |
| 8 | 7 | |
| 9 | 21 | |
| 10 | 5 | |
| 11 | 3 | |
| 12 | 53 | |
| 13 | 218 | |
| 14 | 2 | |
| 15 | 39 | |
| 16 | 2 | |
| 17 | 8 | |
| 18 | 24 | |
| 19 | 20 | |
| 20 | 150 |
About Anika Buchholz
Anika Buchholz is a scholar working on Statistics and Probability, Business and International Management and Endocrine and Autonomic Systems, having authored 27 papers that have together received 758 indexed citations. Recurring topics across this work include Statistical Methods and Inference (7 papers), Health Systems, Economic Evaluations, Quality of Life (6 papers) and Patient-Provider Communication in Healthcare (4 papers). The work is most often cited by research in Endocrine and Autonomic Systems (160 citations), Statistics and Probability (168 citations) and Physiology (223 citations). Anika Buchholz has collaborated with scholars based in Germany, France and United Kingdom. Frequent co-authors include Martin Schumacher, Willi Sauerbrei, Jan Beyersmann, Aurélien Latouche, Karl Wegscheider, Henrik Fox, Dieter Horstkotte, Birgit Wellmann, Thomas Bitter and Olaf Oldenburg. Their work appears in journals such as PLoS ONE, The Plant Cell and Stroke.
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.