Dannis G. van Vuurden
- Genetics top 1%
- Glioma Diagnosis and Treatment 49
- Neurology top 2%
- Neuroblastoma Research and Treatments 14
- Cancer Research top 10%
- Developmental Neuroscience top 10%
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- Childhood Cancer Survivors' Quality of Life 7
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- Radiomics and Machine Learning in Medical Imaging 6
- MRI in cancer diagnosis 3
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- Ultrasound and Hyperthermia Applications 5
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- Meningioma and schwannoma management 4
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- Brain Metastases and Treatment 3
- Co-authors
- Gertjan J.L. KaspersW. Peter VandertopMarc H.A. JansenEsther HullemanDavid P. NoskeSophie E. M. Veldhuijzen van ZantenThomas WürdingerLaurine E. Wedekind
- Cited by
- GeneticsNeurologyCancer Research
- Journals
- Journal of Clinical Oncology (3 papers)SHILAP Revista de lepidopterología (2 papers)PLoS ONE (2 papers)
- Partner nations
- NetherlandsUnited StatesGermany
In The Last Decade
Dannis G. van Vuurden
63 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 99
- Genetics 968
- Neurology 454
- Cancer Research 187
- Developmental Neuroscience 44
- Pediatrics, Perinatology and Child Health 203
Countries citing papers authored by Dannis G. van Vuurden
This map shows the geographic impact of Dannis G. van Vuurden'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 Dannis G. van Vuurden with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dannis G. van Vuurden more than expected).
Fields of papers citing papers by Dannis G. van Vuurden
This network shows the impact of papers produced by Dannis G. van Vuurden. 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 Dannis G. van Vuurden. The network helps show where Dannis G. van Vuurden may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dannis G. van Vuurden, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 2 | |
| 2 | 2024 | 6 | |
| 3 | 2023 | 3 | |
| 4 | 2023 | 13 | |
| 5 | 2022 | 11 | |
| 6 | 2021 | 5 | |
| 7 | 2021 | 7 | |
| 8 | 2021 | 4 | |
| 9 | 2020 | 99 | |
| 10 | 2018 | 32 | |
| 11 | 2017 | 19 | |
| 12 | 2017 | 89 | |
| 13 | 2016 | 50 | |
| 14 | 2016 | 17 | |
| 15 | 2015 | 19 | |
| 16 | 2015 | 13 | |
| 17 | 2014 | 37 | |
| 18 | 2013 | 106 | |
| 19 | 2012 | 58 | |
| 20 | 2011 | 151 |
About Dannis G. van Vuurden
Dannis G. van Vuurden is a scholar working on Genetics, Developmental Neuroscience and Neurology, having authored 69 papers that have together received 1.7k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (49 papers), Neuroblastoma Research and Treatments (14 papers), Childhood Cancer Survivors' Quality of Life (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Ultrasound and Hyperthermia Applications (5 papers), Meningioma and schwannoma management (4 papers), MRI in cancer diagnosis (3 papers) and Brain Metastases and Treatment (3 papers). The work is most often cited by research in Genetics (968 citations), Neurology (454 citations) and Cancer Research (187 citations). Dannis G. van Vuurden has collaborated with scholars based in Netherlands, United States and Germany. Frequent co-authors include Gertjan J.L. Kaspers, W. Peter Vandertop, Marc H.A. Jansen, Esther Hulleman, David P. Noske, Sophie E. M. Veldhuijzen van Zanten, Thomas Würdinger, Laurine E. Wedekind, Pieter Wesseling and Bernd Granzen. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and PLoS ONE.
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.