Mirjam Jonkman
Impact in
- Health Information Management top 0.2%
- Artificial Intelligence in Healthcare
- Health Informatics top 5%
Papers in
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- AI in cancer detection 16
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- ECG Monitoring and Analysis 12
- Co-authors
- Sami Azam (63 shared papers)Friso De Boer (44 shared papers)Asif Karim (26 shared papers)Pronab Ghosh (7 shared papers)Mohamed Elgendi (10 shared papers)Abhijith Reddy Beeravolu (4 shared papers)Bharanidharan Shanmugam (17 shared papers)Eva Ignatious (5 shared papers)
- Journals
- IEEE Access (8 papers)Intelligent Systems with Applications (4 papers)Biomedicines (4 papers)PLoS ONE (2 papers)Heliyon (2 papers)
- Partner nations
- AustraliaBangladeshCanada
In The Last Decade
Mirjam Jonkman
77 papers receiving 1.6k citations
Mirjam Jonkman's Hit Papers
Peers
Comparison fields: 5 of 148
- Health Information Management 336
- Health Informatics 27
- Artificial Intelligence 551
- Cardiology and Cardiovascular Medicine 302
- Radiology, Nuclear Medicine and Imaging 303
Countries citing papers authored by Mirjam Jonkman
This map shows the geographic impact of Mirjam Jonkman'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 Mirjam Jonkman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mirjam Jonkman more than expected).
Fields of papers citing papers by Mirjam Jonkman
This network shows the impact of papers produced by Mirjam Jonkman. 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 Mirjam Jonkman. The network helps show where Mirjam Jonkman may publish in the future.
Co-authors
The 25 scholars most cited alongside Mirjam Jonkman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Efficient Prediction of Cardiovascular Disease Using Machine Learning Algorithms With Relief and LASSO Feature Selection Techniques Hit paper breakdown → | 2021 | 341 |
| 2 | 2010 | 92 | |
| 3 | 2021 | 82 | |
| 4 | 2021 | 79 | |
| 5 | 2023 | 59 | |
| 6 | 2019 | 50 | |
| 7 | 2021 | 49 | |
| 8 | 2021 | 43 | |
| 9 | 2022 | 39 | |
| 10 | 2021 | 37 | |
| 11 | 2023 | 36 | |
| 12 | 2009 | 33 | |
| 13 | 2022 | 32 | |
| 14 | 2020 | 31 | |
| 15 | 2022 | 31 | |
| 16 | 2023 | 30 | |
| 17 | 2019 | 30 | |
| 18 | 2019 | 28 | |
| 19 | 2019 | 27 | |
| 20 | 2021 | 27 |
About Mirjam Jonkman
Mirjam Jonkman is a scholar working on Artificial Intelligence, Cardiology and Cardiovascular Medicine, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Information Systems, having authored 79 papers that have together received 1.7k indexed citations. Recurring topics across this work include AI in cancer detection (16 papers), ECG Monitoring and Analysis (12 papers), Non-Invasive Vital Sign Monitoring (8 papers), EEG and Brain-Computer Interfaces (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Digital Imaging for Blood Diseases (6 papers), Blockchain Technology Applications and Security (6 papers) and Artificial Intelligence in Healthcare (6 papers). The work is most often cited by research in Health Information Management (336 citations), Health Informatics (27 citations), Artificial Intelligence (551 citations), Cardiology and Cardiovascular Medicine (302 citations) and Radiology, Nuclear Medicine and Imaging (303 citations). Mirjam Jonkman has collaborated with scholars based in Australia, Bangladesh and Canada. Frequent co-authors include Sami Azam, Friso De Boer, Asif Karim, Pronab Ghosh, Mohamed Elgendi, Abhijith Reddy Beeravolu, Bharanidharan Shanmugam, Eva Ignatious, F. M. Javed Mehedi Shamrat and Sidratul Montaha. Their work appears in journals such as IEEE Access, Intelligent Systems with Applications, Biomedicines, PLoS ONE and Heliyon.
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.