Malte Jensen
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Monoclonal and Polyclonal Antibodies Research
- Retinal Imaging and Analysis
Papers in
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- Radiomics and Machine Learning in Medical Imaging 3
- Monoclonal and Polyclonal Antibodies Research 2
- Medical Imaging Techniques and Applications 2
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- AI in cancer detection 2
- Co-authors
- Matthew P. Lungren (2 shared papers)Shih-Cheng Huang (3 shared papers)Serena Yeung (2 shared papers)Akshay Chaudhari (3 shared papers)Anuj Pareek (1 shared paper)Andreas Kjær (5 shared papers)Babak Bakhshinejad (2 shared papers)Jacob K. Jensen (2 shared papers)
- Journals
- npj Digital Medicine (1 paper)EJNMMI Physics (1 paper)Journal of Nuclear Cardiology (1 paper)Viruses (1 paper)Scientific Data (1 paper)
- Partner nations
- DenmarkUnited StatesUnited Kingdom
In The Last Decade
Malte Jensen
8 papers receiving 236 citations
Malte Jensen's Hit Papers
Peers
Comparison fields: 5 of 61
- Health Informatics 24
- Radiology, Nuclear Medicine and Imaging 101
- Artificial Intelligence 75
- Health Information Management 9
- Neurology 15
Countries citing papers authored by Malte Jensen
This map shows the geographic impact of Malte Jensen'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 Malte Jensen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Malte Jensen more than expected).
Fields of papers citing papers by Malte Jensen
This network shows the impact of papers produced by Malte Jensen. 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 Malte Jensen. The network helps show where Malte Jensen may publish in the future.
Co-authors
The 16 scholars most cited alongside Malte Jensen, 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 | Self-supervised learning for medical image classification: a systematic review and implementation guidelines Hit paper breakdown → | 2023 | 202 |
| 2 | 2022 | 15 | |
| 3 | 2024 | 7 | |
| 4 | 2022 | 7 | |
| 5 | 2022 | 4 | |
| 6 | 2025 | 4 | |
| 7 | 2024 | 2 | |
| 8 | 2025 | 1 |
About Malte Jensen
Malte Jensen is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Molecular Biology, Pulmonary and Respiratory Medicine and Ecology, having authored 8 papers that have together received 242 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Medical Imaging Techniques and Applications (2 papers), AI in cancer detection (2 papers), Artificial Intelligence in Healthcare and Education (1 paper), Protein purification and stability (1 paper), Cerebrovascular and Carotid Artery Diseases (1 paper) and Bacteriophages and microbial interactions (1 paper). The work is most often cited by research in Health Informatics (24 citations), Radiology, Nuclear Medicine and Imaging (101 citations), Artificial Intelligence (75 citations), Health Information Management (9 citations) and Neurology (15 citations). Malte Jensen has collaborated with scholars based in Denmark, United States and United Kingdom. Frequent co-authors include Matthew P. Lungren, Shih-Cheng Huang, Serena Yeung, Akshay Chaudhari, Anuj Pareek, Andreas Kjær, Babak Bakhshinejad, Jacob K. Jensen, Mikkel Baldtzer Liisberg and Maria Rossing. Their work appears in journals such as npj Digital Medicine, EJNMMI Physics, Journal of Nuclear Cardiology, Viruses and Scientific Data.
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.