Maja von Cube

1.1k citations
24 papers · 331 indexed · h-index 10
Topics
COVID-19 Clinical Research Studies (5 papers)Health Systems, Economic Evaluations, Quality of Life (5 papers)Statistical Methods and Bayesian Inference (4 papers)
Partner nations
GermanyFranceSpain

In The Last Decade

Maja von Cube

23 papers receiving 326 citations

Peers

Maja von Cube
Comparison fields: 5 of 81
  • Infectious Diseases 109
  • Epidemiology 74
  • Economics and Econometrics 65
  • Critical Care and Intensive Care Medicine 59
  • Statistics and Probability 53
Replace Golnar Sabetian with:
Golnar Sabetian Iran
Falk Fichtner Germany
Qin Sun China
Suzana M. Lobo Brazil
Ramesh Vishwakarma Saudi Arabia
Xiao Qing Wang United States
David W. Hsia United States
Rachel Byford United Kingdom
Alexandra B. Spicer United States
Cécile Payet France
Maja von Cube relative to Golnar Sabetian Iran Golnar Sabetian's profile →
Citations per field
00.5×8.8×
Golnar Sabetian · 1×
Citations per year

Countries citing papers authored by Maja von Cube

Since Specialization
Citations

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

Fields of papers citing papers by Maja von Cube

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maja von Cube. 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 Maja von Cube. The network helps show where Maja von Cube may publish in the future.

Co-authorship network of co-authors of Maja von Cube

This figure shows the co-authorship network connecting the top 25 collaborators of Maja von Cube. A scholar is included among the top collaborators of Maja von Cube 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 Maja von Cube. Maja von Cube 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
#WorkIndexed citations
1 4
2 8
3 9
4 3
5 5
6 16
7 8
8 14
9 10
10 66
11 14
12 45
13 34
14 4
15 5
16 10
17 33
18 24
19 4
20 0

About Maja von Cube

Maja von Cube is a scholar working on Statistics and Probability, Critical Care and Intensive Care Medicine and Modeling and Simulation, having authored 24 papers that have together received 331 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (5 papers), Health Systems, Economic Evaluations, Quality of Life (5 papers) and Statistical Methods and Bayesian Inference (4 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (59 citations), Applied Microbiology and Biotechnology (15 citations) and Modeling and Simulation (32 citations). Maja von Cube has collaborated with scholars based in Germany, France and Spain. Frequent co-authors include Martin Wolkewitz, Martin Schumacher, Derek Hazard, Klaus Kaier, Jérôme Lambert, Siegbert Rieg, Adrian Barnett, Nicole White, Winfried V. Kern and Johannes Kalbhenn. Their work appears in journals such as PLoS ONE, Clinical Infectious Diseases and Critical Care Medicine.

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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