Uri Kartoun
- Epidemiology
- Cardiology and Cardiovascular Medicine
- Hepatology top 10%
- Surgery
- Endocrinology, Diabetes and Metabolism
- Co-authors
- Kenney NgStanley Y. ShawKathleen E. CoreyHui ZhengAmit V. KheraAniruddh P. PatelMinxian WangRahul Aggarwal
- Topics
- Machine Learning in Healthcare (6 papers)Liver Disease Diagnosis and Treatment (6 papers)Liver Disease and Transplantation (4 papers)
- Partner nations
- United StatesIrelandJapan
In The Last Decade
Uri Kartoun
29 papers receiving 421 citations
Peers
Comparison fields: 5 of 91
- Epidemiology 139
- Cardiology and Cardiovascular Medicine 122
- Hepatology 87
- Surgery 72
- Endocrinology, Diabetes and Metabolism 67
Countries citing papers authored by Uri Kartoun
This map shows the geographic impact of Uri Kartoun'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 Uri Kartoun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Uri Kartoun more than expected).
Fields of papers citing papers by Uri Kartoun
This network shows the impact of papers produced by Uri Kartoun. 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 Uri Kartoun. The network helps show where Uri Kartoun may publish in the future.
Co-authorship network of co-authors of Uri Kartoun
This figure shows the co-authorship network connecting the top 25 collaborators of Uri Kartoun. A scholar is included among the top collaborators of Uri Kartoun 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 Uri Kartoun. Uri Kartoun 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 | 0 | |
| 3 | 2 | |
| 4 | 10 | |
| 5 | 101 | |
| 6 | 14 | |
| 7 | 40 | |
| 8 | 11 | |
| 9 | 11 | |
| 10 | 2 | |
| 11 | 12 | |
| 12 | 4 | |
| 13 | 14 | |
| 14 | 43 | |
| 15 | The Spectrum of Insomnia-Associated Comorbidities in an Electronic Medical Records Cohort. | 1 |
| 16 | 19 | |
| 17 | Demonstrating the Advantages of Applying Data Mining Techniques on Time-Dependent Electronic Medical Records. | 4 |
| 18 | 61 | |
| 19 | 13 | |
| 20 | A PROTOTYPE FUZZY SYSTEM FOR SURVEILLANCE PICTURE UNDERSTANDING | 3 |
About Uri Kartoun
Uri Kartoun is a scholar working on Health Information Management, Hepatology and Statistics and Probability, having authored 33 papers that have together received 436 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (6 papers), Liver Disease Diagnosis and Treatment (6 papers) and Liver Disease and Transplantation (4 papers). The work is most often cited by research in Health Informatics (16 citations), Hepatology (87 citations) and Health Information Management (33 citations). Uri Kartoun has collaborated with scholars based in United States, Ireland and Japan. Frequent co-authors include Kenney Ng, Stanley Y. Shaw, Kathleen E. Corey, Hui Zheng, Amit V. Khera, Aniruddh P. Patel, Minxian Wang, Rahul Aggarwal, Tracey G. Simon and Patrick T. Ellinor. Their work appears in journals such as Circulation, Gastroenterology and Journal of the American College of Cardiology.
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.