Mart van Rijthoven
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Oncology
- Biophysics top 5%
- Co-authors
- Jeroen van der LaakFrancesco CiompiMaschenka BalkenholKarīna SiliņaŻaneta Świderska-ChadajGeert LitjensQuirine F. MansonHans Pinckaers
- Topics
- AI in cancer detection (7 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)Digital Imaging for Blood Diseases (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaMedical Image Analysisnpj Digital Medicine
- Partner nations
- NetherlandsSwitzerlandSweden
In The Last Decade
Mart van Rijthoven
8 papers receiving 326 citations
Peers
Comparison fields: 5 of 52
- Artificial Intelligence 231
- Radiology, Nuclear Medicine and Imaging 169
- Computer Vision and Pattern Recognition 116
- Oncology 76
- Biophysics 53
Countries citing papers authored by Mart van Rijthoven
This map shows the geographic impact of Mart van Rijthoven'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 Mart van Rijthoven with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mart van Rijthoven more than expected).
Fields of papers citing papers by Mart van Rijthoven
This network shows the impact of papers produced by Mart van Rijthoven. 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 Mart van Rijthoven. The network helps show where Mart van Rijthoven may publish in the future.
Co-authorship network of co-authors of Mart van Rijthoven
This figure shows the co-authorship network connecting the top 25 collaborators of Mart van Rijthoven. A scholar is included among the top collaborators of Mart van Rijthoven 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 Mart van Rijthoven. Mart van Rijthoven is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 21 | |
| 2 | 40 | |
| 3 | 134 | |
| 4 | 1 | |
| 5 | 14 | |
| 6 | 104 | |
| 7 | You Only Look on Lymphocytes Once | 14 |
| 8 | Convolutional Neural Networks for Lymphocyte detection in Immunohistochemically Stained Whole-Slide Images | 10 |
About Mart van Rijthoven
Mart van Rijthoven is a scholar working on Biophysics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 8 papers that have together received 338 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Digital Imaging for Blood Diseases (4 papers). The work is most often cited by research in Biophysics (53 citations), Health Informatics (11 citations) and Radiology, Nuclear Medicine and Imaging (169 citations). Mart van Rijthoven has collaborated with scholars based in Netherlands, Switzerland and Sweden. Frequent co-authors include Jeroen van der Laak, Francesco Ciompi, Maschenka Balkenhol, Karīna Siliņa, Żaneta Świderska-Chadaj, Geert Litjens, Quirine F. Manson, Hans Pinckaers, Oscar Geessink and António Polónia. Their work appears in journals such as SHILAP Revista de lepidopterología, Medical Image Analysis and npj Digital 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.