Fred Prior
- Health Informatics top 0.2%
- Artificial Intelligence in Healthcare and Education 9
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- Radiomics and Machine Learning in Medical Imaging 24
- Medical Imaging Techniques and Applications 11
- Neurology top 2%
- Cognitive Neuroscience top 2%
- Functional Brain Connectivity Studies 9
- Artificial Intelligence top 0.5%
- AI in cancer detection 16
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- Digital Radiography and Breast Imaging 17
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- Biomedical Text Mining and Ontologies 12
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- Diabetic Foot Ulcer Assessment and Management 11
Fred Prior
109 papers receiving 6.2k citations
Hit Papers
Peers
Comparison fields: 5 of 173
- Health Informatics 364
- Radiology, Nuclear Medicine and Imaging 3.3k
- Neurology 435
- Cognitive Neuroscience 947
- Artificial Intelligence 1.4k
Countries citing papers authored by Fred Prior
This map shows the geographic impact of Fred Prior'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 Fred Prior with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fred Prior more than expected).
Fields of papers citing papers by Fred Prior
This network shows the impact of papers produced by Fred Prior. 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 Fred Prior. The network helps show where Fred Prior may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fred Prior, 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 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 12 | |
| 6 | 2023 | 0 | |
| 7 | 2022 | 10 | |
| 8 | 2022 | 1 | |
| 9 | 2021 | 20 | |
| 10 | 2021 | 12 | |
| 11 | 2020 | 35 | |
| 12 | 2020 | 11 | |
| 13 | 2020 | 1 | |
| 14 | 2017 | 14 | |
| 15 | A re-evaluation of the Down syndrome diagnosis for LB1 (Homo floresiensis) | 2015 | 3 |
| 16 | The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repositorybreakdown → | 2013 | 2948 |
| 17 | 2012 | 18 | |
| 18 | 2010 | 34 | |
| 19 | 2009 | 64 | |
| 20 | 1997 | 253 |
About Fred Prior
Fred Prior is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Information Systems and Management, having authored 116 papers that have together received 6.3k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (24 papers), Digital Radiography and Breast Imaging (17 papers), AI in cancer detection (16 papers), Biomedical Text Mining and Ontologies (12 papers), Medical Imaging Techniques and Applications (11 papers), Diabetic Foot Ulcer Assessment and Management (11 papers), Functional Brain Connectivity Studies (9 papers) and Artificial Intelligence in Healthcare and Education (9 papers). The work is most often cited by research in Health Informatics (364 citations), Radiology, Nuclear Medicine and Imaging (3.3k citations) and Neurology (435 citations). Fred Prior has collaborated with scholars based in United States, United Kingdom and Spain. Frequent co-authors include Kirk Smith, Justin Kirby, John Freymann, Lawrence Tarbox, Kenneth Clark, Stephen Moore, Bruce A. Vendt, Paul Koppel, Michael Pringle and Linda Larson‐Prior. Their work appears in journals such as Journal of Digital Imaging, Medical Physics, Scientific Reports, Scientific Data and American Journal of Physical Anthropology.
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.