Heidi Daniel
Impact in
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- MRI in cancer diagnosis
- Radiomics and Machine Learning in Medical Imaging
- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Medical Imaging Techniques and Applications
Papers in
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- MRI in cancer diagnosis 10
- Advanced Neuroimaging Techniques and Applications 2
- Advanced MRI Techniques and Applications 2
- Radiomics and Machine Learning in Medical Imaging 1
- Medical Imaging Techniques and Applications 1
- Co-authors
- Wolfgang Lederer (10 shared papers)Frederik B. Laun (10 shared papers)Sebastian Bickelhaupt (10 shared papers)Stefan Delorme (8 shared papers)Heinz-Peter Schlemmer (4 shared papers)Daniel Paech (4 shared papers)Anne Stieber (5 shared papers)Klaus Maier‐Hein (4 shared papers)
- Journals
- Radiology (2 papers)Scientific Reports (1 paper)RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren (1 paper)European Radiology (1 paper)Clinical Radiology (1 paper)
- Partner nations
- GermanyFranceNew Zealand
In The Last Decade
Heidi Daniel
10 papers receiving 383 citations
Peers
Comparison fields: 5 of 33
- Radiology, Nuclear Medicine and Imaging 318
- Health Informatics 5
- Artificial Intelligence 58
- Oncology 19
- Pulmonary and Respiratory Medicine 21
Countries citing papers authored by Heidi Daniel
This map shows the geographic impact of Heidi Daniel'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 Heidi Daniel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heidi Daniel more than expected).
Fields of papers citing papers by Heidi Daniel
This network shows the impact of papers produced by Heidi Daniel. 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 Heidi Daniel. The network helps show where Heidi Daniel may publish in the future.
Co-authors
The 25 scholars most cited alongside Heidi Daniel, 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 | 2017 | 114 | |
| 2 | 2015 | 100 | |
| 3 | 2018 | 81 | |
| 4 | 2016 | 33 | |
| 5 | 2017 | 29 | |
| 6 | 2017 | 15 | |
| 7 | 2020 | 5 | |
| 8 | 2016 | 5 | |
| 9 | 2019 | 3 | |
| 10 | 2019 | 1 |
About Heidi Daniel
Heidi Daniel is a scholar working on Radiology, Nuclear Medicine and Imaging, Infectious Diseases, Organic Chemistry, Surgery and Communication, having authored 10 papers that have together received 386 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (10 papers), Advanced Neuroimaging Techniques and Applications (2 papers), Advanced MRI Techniques and Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (318 citations), Health Informatics (5 citations), Artificial Intelligence (58 citations), Oncology (19 citations) and Pulmonary and Respiratory Medicine (21 citations). Heidi Daniel has collaborated with scholars based in Germany, France and New Zealand. Frequent co-authors include Wolfgang Lederer, Frederik B. Laun, Sebastian Bickelhaupt, Stefan Delorme, Heinz-Peter Schlemmer, Daniel Paech, Anne Stieber, Klaus Maier‐Hein, Heinz‐Peter Schlemmer and David Bonekamp. Their work appears in journals such as Radiology, Scientific Reports, RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, European Radiology and Clinical 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.