Ole-Johan Skrede
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Artificial Intelligence in Healthcare and Education 1
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- Radiomics and Machine Learning in Medical Imaging 2
- COVID-19 diagnosis using AI 1
- Co-authors
- Knut Liestøl (4 shared papers)Andreas Kleppe (4 shared papers)Havard Emil Danielsen (4 shared papers)Sepp de Raedt (3 shared papers)David James Kerr (3 shared papers)Arild Nesbakken (2 shared papers)Tarjei S. Hveem (2 shared papers)David N. Church (2 shared papers)
- Journals
- Nature reviews. Cancer (1 paper)The Lancet Oncology (1 paper)Nature Machine Intelligence (1 paper)EClinicalMedicine (1 paper)The Lancet (1 paper)
- Partner nations
- United KingdomNorwayNetherlands
In The Last Decade
Ole-Johan Skrede
4 papers receiving 786 citations
Ole-Johan Skrede's Hit Papers
Peers
Comparison fields: 5 of 84
- Health Informatics 81
- Radiology, Nuclear Medicine and Imaging 332
- Artificial Intelligence 339
- Oncology 202
- Cancer Research 104
Countries citing papers authored by Ole-Johan Skrede
This map shows the geographic impact of Ole-Johan Skrede'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 Ole-Johan Skrede with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ole-Johan Skrede more than expected).
Fields of papers citing papers by Ole-Johan Skrede
This network shows the impact of papers produced by Ole-Johan Skrede. 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 Ole-Johan Skrede. The network helps show where Ole-Johan Skrede may publish in the future.
Co-authors
The 21 scholars most cited alongside Ole-Johan Skrede, 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 | Deep learning for prediction of colorectal cancer outcome: a discovery and validation study Hit paper breakdown → | 2020 | 479 |
| 2 | Designing deep learning studies in cancer diagnostics Hit paper breakdown → | 2021 | 254 |
| 3 | 2022 | 69 | |
| 4 | 2024 | 1 | |
| 5 | 2026 | 0 |
About Ole-Johan Skrede
Ole-Johan Skrede is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Insect Science and Renewable Energy, Sustainability and the Environment, having authored 5 papers that have together received 803 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (2 papers), AI in cancer detection (1 paper), COVID-19 diagnosis using AI (1 paper), Machine Learning in Healthcare (1 paper) and Artificial Intelligence in Healthcare and Education (1 paper). The work is most often cited by research in Health Informatics (81 citations), Radiology, Nuclear Medicine and Imaging (332 citations), Artificial Intelligence (339 citations), Oncology (202 citations) and Cancer Research (104 citations). Ole-Johan Skrede has collaborated with scholars based in United Kingdom, Norway and Netherlands. Frequent co-authors include Knut Liestøl, Andreas Kleppe, Havard Emil Danielsen, Sepp de Raedt, David James Kerr, Arild Nesbakken, Tarjei S. Hveem, David N. Church, Rachel S. Kerr and Hanne Arenberg Askautrud. Their work appears in journals such as Nature reviews. Cancer, The Lancet Oncology, Nature Machine Intelligence, EClinicalMedicine and The Lancet.
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.