Maria Sudell
- Psychiatry and Mental health top 5%
- Pediatrics, Perinatology and Child Health top 10%
- Cellular and Molecular Neuroscience
- Statistics and Probability top 10%
- Oncology
- Co-authors
- Catrin Tudur SmithSarah J NevittAnthony G MarsonJennifer WestonRuwanthi Kolamunnage‐DonaMaroeska M. RoversAlfonso IorioRichard D Riley
- Topics
- Epilepsy research and treatment (5 papers)Pharmacological Effects and Toxicity Studies (5 papers)Statistical Methods and Bayesian Inference (3 papers)
- Cited by
- Psychiatry and Mental healthPediatrics, Perinatology and Child HealthStatistics and Probability
- Partner nations
- United KingdomFranceNetherlands
In The Last Decade
Maria Sudell
12 papers receiving 421 citations
Peers
Comparison fields: 5 of 112
- Psychiatry and Mental health 201
- Pediatrics, Perinatology and Child Health 185
- Cellular and Molecular Neuroscience 49
- Statistics and Probability 46
- Oncology 35
Countries citing papers authored by Maria Sudell
This map shows the geographic impact of Maria Sudell'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 Maria Sudell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maria Sudell more than expected).
Fields of papers citing papers by Maria Sudell
This network shows the impact of papers produced by Maria Sudell. 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 Maria Sudell. The network helps show where Maria Sudell may publish in the future.
Co-authorship network of co-authors of Maria Sudell
This figure shows the co-authorship network connecting the top 25 collaborators of Maria Sudell. A scholar is included among the top collaborators of Maria Sudell 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 Maria Sudell. Maria Sudell is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 31 | |
| 3 | 2 | |
| 4 | 6 | |
| 5 | 2 | |
| 6 | 116 | |
| 7 | 2 | |
| 8 | 80 | |
| 9 | 36 | |
| 10 | 111 | |
| 11 | 11 | |
| 12 | 29 |
About Maria Sudell
Maria Sudell is a scholar working on Statistics and Probability, Psychiatry and Mental health and Statistics, Probability and Uncertainty, having authored 12 papers that have together received 427 indexed citations. Recurring topics across this work include Epilepsy research and treatment (5 papers), Pharmacological Effects and Toxicity Studies (5 papers) and Statistical Methods and Bayesian Inference (3 papers). The work is most often cited by research in Psychiatry and Mental health (201 citations), Pediatrics, Perinatology and Child Health (185 citations) and Statistics and Probability (46 citations). Maria Sudell has collaborated with scholars based in United Kingdom, France and Netherlands. Frequent co-authors include Catrin Tudur Smith, Sarah J Nevitt, Anthony G Marson, Jennifer Weston, Ruwanthi Kolamunnage‐Dona, Maroeska M. Rovers, Alfonso Iorio, Richard D Riley, Paula Williamson and Maura Marcucci. Their work appears in journals such as Cochrane Database of Systematic Reviews, Statistics in Medicine and Epilepsia.
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.