Dennis Bontempi
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- Advanced MRI Techniques and Applications
- COVID-19 diagnosis using AI
- Medical Imaging Techniques and Applications
Papers in
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- Radiomics and Machine Learning in Medical Imaging 8
- Medical Imaging Techniques and Applications 2
- COVID-19 diagnosis using AI 1
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- Advanced X-ray and CT Imaging 2
- Medical Imaging and Analysis 2
- Co-authors
- Raymond H. Mak (6 shared papers)Hugo J.W.L. Aerts (7 shared papers)Mateo Sokač (1 shared paper)Tafadzwa L. Chaunzwa (1 shared paper)Suraj Pai (2 shared papers)Simon Bernatz (1 shared paper)Ahmed Hosny (2 shared papers)Nicolai J. Birkbak (1 shared paper)
- Journals
- Nature Communications (2 papers)Cancers (1 paper)Frontiers in Oncology (1 paper)International Journal of Radiation Oncology*Biology*Physics (1 paper)The Lancet Digital Health (1 paper)
- Partner nations
- United StatesNetherlandsCanada
In The Last Decade
Dennis Bontempi
8 papers receiving 109 citations
Dennis Bontempi's Hit Papers
Peers
Comparison fields: 5 of 49
- Health Informatics 20
- Radiology, Nuclear Medicine and Imaging 70
- Health Information Management 6
- Artificial Intelligence 34
- Structural Biology 1
Countries citing papers authored by Dennis Bontempi
This map shows the geographic impact of Dennis Bontempi'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 Dennis Bontempi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dennis Bontempi more than expected).
Fields of papers citing papers by Dennis Bontempi
This network shows the impact of papers produced by Dennis Bontempi. 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 Dennis Bontempi. The network helps show where Dennis Bontempi may publish in the future.
Co-authors
The 25 scholars most cited alongside Dennis Bontempi, 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 | Foundation model for cancer imaging biomarkers Hit paper breakdown → | 2024 | 63 |
| 2 | 2023 | 18 | |
| 3 | 2021 | 15 | |
| 4 | 2024 | 6 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 2 | |
| 7 | 2022 | 2 | |
| 8 | 2022 | 1 | |
| 9 | 2024 | 0 | |
| 10 | 2025 | 0 |
About Dennis Bontempi
Dennis Bontempi is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Pulmonary and Respiratory Medicine, Artificial Intelligence and Health Informatics, having authored 10 papers that have together received 109 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (8 papers), AI in cancer detection (3 papers), Lung Cancer Diagnosis and Treatment (2 papers), Medical Imaging Techniques and Applications (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Advanced X-ray and CT Imaging (2 papers), Medical Imaging and Analysis (2 papers) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Health Informatics (20 citations), Radiology, Nuclear Medicine and Imaging (70 citations), Health Information Management (6 citations), Artificial Intelligence (34 citations) and Structural Biology (1 citation). Dennis Bontempi has collaborated with scholars based in United States, Netherlands and Canada. Frequent co-authors include Raymond H. Mak, Hugo J.W.L. Aerts, Mateo Sokač, Tafadzwa L. Chaunzwa, Suraj Pai, Simon Bernatz, Ahmed Hosny, Nicolai J. Birkbak, Sergio Benini and Lars Muckli. Their work appears in journals such as Nature Communications, Cancers, Frontiers in Oncology, International Journal of Radiation Oncology*Biology*Physics and The Lancet Digital Health.
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.