Eva‐Maria Didden
Impact in
- Health Information Management top 10%
- Electronic Health Records Systems
- Medical Coding and Health Information
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- Artificial Intelligence in Healthcare and Education
Papers in
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- Electronic Health Records Systems 3
- Medical Coding and Health Information 3
- Artificial Intelligence in Healthcare 1
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- Pulmonary Hypertension Research and Treatments 6
- Co-authors
- Rose Chik-ying Ong (2 shared papers)Noemi Hummel (2 shared papers)Matthias Egger (2 shared papers)Stephan Reichenbach (2 shared papers)Mette Nørgaard (1 shared paper)Katalin Veres (1 shared paper)David Wormser (2 shared papers)Melinda Magyari (1 shared paper)
- Journals
- Pulmonary Circulation (3 papers)Neurology (1 paper)Multiple Sclerosis and Related Disorders (1 paper)EClinicalMedicine (1 paper)Respiratory Research (1 paper)
- Partner nations
- SwitzerlandUnited KingdomUnited States
In The Last Decade
Eva‐Maria Didden
14 papers receiving 288 citations
Peers
Comparison fields: 5 of 47
- Health Information Management 50
- Health Informatics 13
- Rheumatology 40
- Pathology and Forensic Medicine 43
- Statistics and Probability 31
Countries citing papers authored by Eva‐Maria Didden
This map shows the geographic impact of Eva‐Maria Didden'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 Eva‐Maria Didden with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eva‐Maria Didden more than expected).
Fields of papers citing papers by Eva‐Maria Didden
This network shows the impact of papers produced by Eva‐Maria Didden. 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 Eva‐Maria Didden. The network helps show where Eva‐Maria Didden may publish in the future.
Co-authors
The 25 scholars most cited alongside Eva‐Maria Didden, 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 | 56 | |
| 2 | 2021 | 54 | |
| 3 | 2018 | 46 | |
| 4 | 2023 | 26 | |
| 5 | 2022 | 25 | |
| 6 | 2023 | 24 | |
| 7 | 2024 | 20 | |
| 8 | 2020 | 19 | |
| 9 | 2023 | 10 | |
| 10 | 2018 | 7 | |
| 11 | 2015 | 2 | |
| 12 | 2018 | 2 | |
| 13 | 2024 | 2 | |
| 14 | 2024 | 2 | |
| 15 | 2026 | 0 |
About Eva‐Maria Didden
Eva‐Maria Didden is a scholar working on Health Information Management, Pulmonary and Respiratory Medicine, Statistics and Probability, Rheumatology and Artificial Intelligence, having authored 15 papers that have together received 295 indexed citations. Recurring topics across this work include Pulmonary Hypertension Research and Treatments (6 papers), Electronic Health Records Systems (3 papers), Medical Coding and Health Information (3 papers), Rheumatoid Arthritis Research and Therapies (2 papers), Statistical Methods in Clinical Trials (2 papers), Privacy-Preserving Technologies in Data (1 paper), Advanced Vision and Imaging (1 paper) and Artificial Intelligence in Healthcare (1 paper). The work is most often cited by research in Health Information Management (50 citations), Health Informatics (13 citations), Rheumatology (40 citations), Pathology and Forensic Medicine (43 citations) and Statistics and Probability (31 citations). Eva‐Maria Didden has collaborated with scholars based in Switzerland, United Kingdom and United States. Frequent co-authors include Rose Chik-ying Ong, Noemi Hummel, Matthias Egger, Stephan Reichenbach, Mette Nørgaard, Katalin Veres, David Wormser, Melinda Magyari, Deborah A. Quinn and Monika Brand. Their work appears in journals such as Pulmonary Circulation, Neurology, Multiple Sclerosis and Related Disorders, EClinicalMedicine and Respiratory Research.
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.