Mehmet Aydar
- Cardiology and Cardiovascular Medicine top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Health Informatics top 0.5%
- Artificial Intelligence top 5%
- Health Information Management top 0.5%
- Co-authors
- Chayakrit KrittanawongZhen WangTakeshi KitaiHongJu ZhangSanjiv M. NarayanKipp W. JohnsonJonathan L. HalperinUsman Baber
- Topics
- Semantic Web and Ontologies (6 papers)Artificial Intelligence in Healthcare and Education (4 papers)Data Quality and Management (4 papers)
- Partner nations
- United StatesTürkiyeJapan
In The Last Decade
Mehmet Aydar
18 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 132
- Cardiology and Cardiovascular Medicine 363
- Radiology, Nuclear Medicine and Imaging 274
- Health Informatics 243
- Artificial Intelligence 226
- Health Information Management 189
Countries citing papers authored by Mehmet Aydar
This map shows the geographic impact of Mehmet Aydar'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 Mehmet Aydar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mehmet Aydar more than expected).
Fields of papers citing papers by Mehmet Aydar
This network shows the impact of papers produced by Mehmet Aydar. 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 Mehmet Aydar. The network helps show where Mehmet Aydar may publish in the future.
Co-authorship network of co-authors of Mehmet Aydar
This figure shows the co-authorship network connecting the top 25 collaborators of Mehmet Aydar. A scholar is included among the top collaborators of Mehmet Aydar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mehmet Aydar. Mehmet Aydar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 40 | |
| 3 | 21 | |
| 4 | 5 | |
| 5 | 6 | |
| 6 | 81 | |
| 7 | 1 | |
| 8 | Deep learning for cardiovascular medicine: a practical primerbreakdown → | 235 |
| 9 | 11 | |
| 10 | 15 | |
| 11 | Artificial Intelligence in Precision Cardiovascular Medicinebreakdown → | 639 |
| 12 | 4 | |
| 13 | 11 | |
| 14 | 1 | |
| 15 | Translation of Instance Data using RDF and Structured Mapping Definitions. | 1 |
| 16 | RinsMatch: a suggestion-based instance matching system in RDF Graphs. | 1 |
| 17 | 5 | |
| 18 | Automatic Weight Generation and Class Predicate Stability in RDF Summary Graphs. | 4 |
About Mehmet Aydar
Mehmet Aydar is a scholar working on Health Informatics, Health Information Management and Management Science and Operations Research, having authored 18 papers that have together received 1.1k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (6 papers), Artificial Intelligence in Healthcare and Education (4 papers) and Data Quality and Management (4 papers). The work is most often cited by research in Health Informatics (243 citations), Health Information Management (189 citations) and Cardiology and Cardiovascular Medicine (363 citations). Mehmet Aydar has collaborated with scholars based in United States, Türkiye and Japan. Frequent co-authors include Chayakrit Krittanawong, Zhen Wang, Takeshi Kitai, HongJu Zhang, Sanjiv M. Narayan, Kipp W. Johnson, Jonathan L. Halperin, Usman Baber, W.H. Wilson Tang and Robert S. Rosenson. Their work appears in journals such as Journal of the American College of Cardiology, Scientific Reports and European Heart Journal.
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.