P. Whybra
Impact in
-
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- MRI in cancer diagnosis
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
Papers in
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- Radiomics and Machine Learning in Medical Imaging 9
- Medical Imaging Techniques and Applications 1
-
- Brain Tumor Detection and Classification 1
- Co-authors
- Emiliano Spezi (10 shared papers)Kieran Foley (7 shared papers)John Nicholas Staffurth (2 shared papers)Tom David Lewis Crosby (4 shared papers)Zhenwei Shi (3 shared papers)Andre L.A.J. Dekker (3 shared papers)Leonard Wee (3 shared papers)Petros Kalendralis (2 shared papers)
- Journals
- Radiotherapy and Oncology (4 papers)Radiology (2 papers)Scientific Reports (2 papers)Frontiers in Oncology (1 paper)British Journal of Radiology (1 paper)
- Partner nations
- United KingdomNetherlandsGermany
In The Last Decade
P. Whybra
12 papers receiving 3.2k citations
P. Whybra's Hit Papers
Peers
Comparison fields: 5 of 58
- Radiology, Nuclear Medicine and Imaging 2.9k
- Health Informatics 107
- Radiation 42
- Genetics 33
- Neurology 52
Countries citing papers authored by P. Whybra
This map shows the geographic impact of P. Whybra'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 P. Whybra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites P. Whybra more than expected).
Fields of papers citing papers by P. Whybra
This network shows the impact of papers produced by P. Whybra. 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 P. Whybra. The network helps show where P. Whybra may publish in the future.
Co-authors
The 25 scholars most cited alongside P. Whybra, 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 | The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping Hit paper breakdown → | 2020 | 2935 |
| 2 | The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights Hit paper breakdown → | 2024 | 148 |
| 3 | 2019 | 61 | |
| 4 | 2018 | 24 | |
| 5 | 2020 | 22 | |
| 6 | 2020 | 22 | |
| 7 | 2019 | 17 | |
| 8 | 2019 | 10 | |
| 9 | 2018 | 9 | |
| 10 | 2023 | 6 | |
| 11 | 2023 | 5 | |
| 12 | 2018 | 2 |
About P. Whybra
P. Whybra is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology, Surgery, Computer Vision and Pattern Recognition and Nuclear Energy and Engineering, having authored 12 papers that have together received 3.3k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (9 papers), Esophageal Cancer Research and Treatment (2 papers), Medical Imaging Techniques and Applications (1 paper), Medical Image Segmentation Techniques (1 paper) and Brain Tumor Detection and Classification (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (2.9k citations), Health Informatics (107 citations), Radiation (42 citations), Genetics (33 citations) and Neurology (52 citations). P. Whybra has collaborated with scholars based in United Kingdom, Netherlands and Germany. Frequent co-authors include Emiliano Spezi, Kieran Foley, John Nicholas Staffurth, Tom David Lewis Crosby, Zhenwei Shi, Andre L.A.J. Dekker, Leonard Wee, Petros Kalendralis, Maaike Berbée and Chris N Hurt. Their work appears in journals such as Radiotherapy and Oncology, Radiology, Scientific Reports, Frontiers in Oncology and British Journal of Radiology.
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.