Arash Shaban‐Nejad
- Artificial Intelligence top 5%
- Health top 5%
- Sociology and Political Science top 10%
- General Health Professions top 10%
- Epidemiology
- Co-authors
- Olufunto A. OlusanyaNariman AmmarRobert L. DavisChad MeltonDavid L. BuckeridgeRobert A. BednarczykEun Kyong ShinAnya Okhmatovskaia
- Topics
- Biomedical Text Mining and Ontologies (23 papers)Semantic Web and Ontologies (16 papers)Data Quality and Management (9 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Arash Shaban‐Nejad
86 papers receiving 836 citations
Peers
Comparison fields: 5 of 125
- Artificial Intelligence 255
- Health 231
- Sociology and Political Science 145
- General Health Professions 137
- Epidemiology 137
Countries citing papers authored by Arash Shaban‐Nejad
This map shows the geographic impact of Arash Shaban‐Nejad'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 Arash Shaban‐Nejad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arash Shaban‐Nejad more than expected).
Fields of papers citing papers by Arash Shaban‐Nejad
This network shows the impact of papers produced by Arash Shaban‐Nejad. 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 Arash Shaban‐Nejad. The network helps show where Arash Shaban‐Nejad may publish in the future.
Co-authorship network of co-authors of Arash Shaban‐Nejad
This figure shows the co-authorship network connecting the top 25 collaborators of Arash Shaban‐Nejad. A scholar is included among the top collaborators of Arash Shaban‐Nejad 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 Arash Shaban‐Nejad. Arash Shaban‐Nejad 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 | 1 | |
| 4 | 26 | |
| 5 | 4 | |
| 6 | 1 | |
| 7 | 7 | |
| 8 | 6 | |
| 9 | 14 | |
| 10 | 9 | |
| 11 | 7 | |
| 12 | 41 | |
| 13 | 1 | |
| 14 | 7 | |
| 15 | 1 | |
| 16 | 34 | |
| 17 | 6 | |
| 18 | 12 | |
| 19 | Population Health Record: An Informatics Infrastructure for Management, Integration, and Analysis of Large Scale Population Health Data | 1 |
| 20 | 2 |
About Arash Shaban‐Nejad
Arash Shaban‐Nejad is a scholar working on Health Informatics, Health Information Management and Health, having authored 91 papers that have together received 859 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (23 papers), Semantic Web and Ontologies (16 papers) and Data Quality and Management (9 papers). The work is most often cited by research in Health Informatics (46 citations), Health (231 citations) and Health Information Management (58 citations). Arash Shaban‐Nejad has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Olufunto A. Olusanya, Nariman Ammar, Robert L. Davis, Chad Melton, David L. Buckeridge, Robert A. Bednarczyk, Eun Kyong Shin, Anya Okhmatovskaia, Volker Haarslev and Christopher J. O. Baker. Their work appears in journals such as SHILAP Revista de lepidopterología, Blood and PLoS ONE.
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.