Sheila Timp
Impact in
- Artificial Intelligence top 5%
- AI in cancer detection
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- Image Retrieval and Classification Techniques
- Medical Image Segmentation Techniques
Papers in
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- AI in cancer detection 8
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- Image Retrieval and Classification Techniques 3
- Medical Image Segmentation Techniques 2
- Co-authors
- Nico Karssemeijer (8 shared papers)Celia Varela (4 shared papers)Saskia van Engeland (3 shared papers)Peter R. Snoeren (1 shared paper)
- Journals
- Medical Physics (3 papers)IEEE Transactions on Medical Imaging (1 paper)Medical Image Analysis (1 paper)Physics in Medicine and Biology (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1 paper)
- Partner nations
- NetherlandsSpainUnited States
In The Last Decade
Sheila Timp
8 papers receiving 352 citations
Peers
Comparison fields: 5 of 38
- Artificial Intelligence 324
- Computer Vision and Pattern Recognition 189
- Radiology, Nuclear Medicine and Imaging 185
- Oncology 62
- Pulmonary and Respiratory Medicine 60
Countries citing papers authored by Sheila Timp
This map shows the geographic impact of Sheila Timp'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 Sheila Timp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sheila Timp more than expected).
Fields of papers citing papers by Sheila Timp
This network shows the impact of papers produced by Sheila Timp. 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 Sheila Timp. The network helps show where Sheila Timp may publish in the future.
Co-authors
The 4 scholars most cited alongside Sheila Timp, 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 | 2004 | 128 | |
| 2 | 2006 | 64 | |
| 3 | 2007 | 56 | |
| 4 | 2006 | 44 | |
| 5 | 2005 | 32 | |
| 6 | 2010 | 24 | |
| 7 | 2005 | 18 | |
| 8 | 2005 | 2 |
About Sheila Timp
Sheila Timp is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Oncology, Radiology, Nuclear Medicine and Imaging and Molecular Biology, having authored 8 papers that have together received 368 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Colorectal Cancer Screening and Detection (4 papers), Image Retrieval and Classification Techniques (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Medical Image Segmentation Techniques (2 papers), Global Cancer Incidence and Screening (1 paper), Digital Radiography and Breast Imaging (1 paper) and Breast Lesions and Carcinomas (1 paper). The work is most often cited by research in Artificial Intelligence (324 citations), Computer Vision and Pattern Recognition (189 citations), Radiology, Nuclear Medicine and Imaging (185 citations), Oncology (62 citations) and Pulmonary and Respiratory Medicine (60 citations). Sheila Timp has collaborated with scholars based in Netherlands, Spain and United States. Frequent co-authors include Nico Karssemeijer, Celia Varela, Saskia van Engeland and Peter R. Snoeren. Their work appears in journals such as Medical Physics, IEEE Transactions on Medical Imaging, Medical Image Analysis, Physics in Medicine and Biology and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.