Vanya Van Belle
- Artificial Intelligence top 10%
- Statistics and Probability top 2%
- Cancer Research
- Oncology
- Molecular Biology
- Co-authors
- Sabine Van HuffelBen Van CalsterJohan A. K. SuykensKristiaan PelckmansD. TimmermanYvonne VergouweEwout W. SteyerbergPaulo Lisböa
- Topics
- Statistical Methods and Inference (8 papers)Statistical Methods and Bayesian Inference (4 papers)Machine Learning in Healthcare (3 papers)
- Partner nations
- BelgiumUnited KingdomNetherlands
In The Last Decade
Vanya Van Belle
25 papers receiving 659 citations
Peers
Comparison fields: 5 of 125
- Artificial Intelligence 195
- Statistics and Probability 145
- Cancer Research 117
- Oncology 99
- Molecular Biology 94
Countries citing papers authored by Vanya Van Belle
This map shows the geographic impact of Vanya Van Belle'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 Vanya Van Belle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vanya Van Belle more than expected).
Fields of papers citing papers by Vanya Van Belle
This network shows the impact of papers produced by Vanya Van Belle. 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 Vanya Van Belle. The network helps show where Vanya Van Belle may publish in the future.
Co-authorship network of co-authors of Vanya Van Belle
This figure shows the co-authorship network connecting the top 25 collaborators of Vanya Van Belle. A scholar is included among the top collaborators of Vanya Van Belle 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 Vanya Van Belle. Vanya Van Belle is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 41 | |
| 2 | 23 | |
| 3 | 25 | |
| 4 | International workshop on advances in regularization, optimization, kernel methods and support vector machines : theory and applications (ROKS 2013) | 1 |
| 5 | Research directions in interpretable machine learning models | 12 |
| 6 | 21 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | Interval coded scoring systems for survival analysis | 2 |
| 10 | 70 | |
| 11 | 68 | |
| 12 | 40 | |
| 13 | 37 | |
| 14 | 18 | |
| 15 | 126 | |
| 16 | On the use of a clinical kernel in survival analysis | 4 |
| 17 | 44 | |
| 18 | 65 | |
| 19 | Survival SVM: a Practical Scalable Algorithm | 21 |
| 20 | Support vector machines for survival analysis | 35 |
About Vanya Van Belle
Vanya Van Belle is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 25 papers that have together received 691 indexed citations. Recurring topics across this work include Statistical Methods and Inference (8 papers), Statistical Methods and Bayesian Inference (4 papers) and Machine Learning in Healthcare (3 papers). The work is most often cited by research in Statistics and Probability (145 citations), Health Informatics (15 citations) and Health Information Management (47 citations). Vanya Van Belle has collaborated with scholars based in Belgium, United Kingdom and Netherlands. Frequent co-authors include Sabine Van Huffel, Ben Van Calster, Johan A. K. Suykens, Kristiaan Pelckmans, D. Timmerman, Yvonne Vergouwe, Ewout W. Steyerberg, Paulo Lisböa, T. Bourne and Caspar W. N. Looman. Their work appears in journals such as Journal of Clinical Oncology, PLoS ONE and Human Reproduction.
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.