Atiye Sarabi‐Jamab
- Neurology
- Artificial Intelligence
- Management Science and Operations Research top 10%
- Clinical Psychology
- Computational Theory and Mathematics
- Co-authors
- Babak Nadjar AraabiThomas AugustinMostafa Almasi‐DooghaeeFatemeh Sadat MirfazeliSeyed Hamid Reza FaizSeyed Vahid ShariatAmin JahanbakhshiVíctor Pereira-Sánchez
- Topics
- Multi-Criteria Decision Making (4 papers)COVID-19 and Mental Health (2 papers)Bayesian Modeling and Causal Inference (2 papers)
- Cited by
- Management Science and Operations ResearchNeurologyCritical Care and Intensive Care Medicine
- Partner nations
- IranGermanyUnited States
In The Last Decade
Atiye Sarabi‐Jamab
12 papers receiving 142 citations
Peers
Comparison fields: 5 of 63
- Neurology 46
- Artificial Intelligence 42
- Management Science and Operations Research 39
- Clinical Psychology 31
- Computational Theory and Mathematics 24
Countries citing papers authored by Atiye Sarabi‐Jamab
This map shows the geographic impact of Atiye Sarabi‐Jamab'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 Atiye Sarabi‐Jamab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Atiye Sarabi‐Jamab more than expected).
Fields of papers citing papers by Atiye Sarabi‐Jamab
This network shows the impact of papers produced by Atiye Sarabi‐Jamab. 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 Atiye Sarabi‐Jamab. The network helps show where Atiye Sarabi‐Jamab may publish in the future.
Co-authorship network of co-authors of Atiye Sarabi‐Jamab
This figure shows the co-authorship network connecting the top 25 collaborators of Atiye Sarabi‐Jamab. A scholar is included among the top collaborators of Atiye Sarabi‐Jamab 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 Atiye Sarabi‐Jamab. Atiye Sarabi‐Jamab 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 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 27 | |
| 6 | 1 | |
| 7 | 40 | |
| 8 | 5 | |
| 9 | 37 | |
| 10 | 3 | |
| 11 | 26 | |
| 12 | 4 |
About Atiye Sarabi‐Jamab
Atiye Sarabi‐Jamab is a scholar working on Management Science and Operations Research, Pharmacy and Applied Psychology, having authored 12 papers that have together received 147 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (4 papers), COVID-19 and Mental Health (2 papers) and Bayesian Modeling and Causal Inference (2 papers). The work is most often cited by research in Management Science and Operations Research (39 citations), Neurology (46 citations) and Critical Care and Intensive Care Medicine (14 citations). Atiye Sarabi‐Jamab has collaborated with scholars based in Iran, Germany and United States. Frequent co-authors include Babak Nadjar Araabi, Thomas Augustin, Mostafa Almasi‐Dooghaee, Fatemeh Sadat Mirfazeli, Seyed Hamid Reza Faiz, Seyed Vahid Shariat, Amin Jahanbakhshi, Víctor Pereira-Sánchez, Behnam Shariati and Shabnam Nohesara. Their work appears in journals such as PLoS ONE, Scientific Reports and Information Sciences.
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.