Qamar Rayees Khan
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Sociology and Political Science
- Information Systems top 10%
- Social Psychology
- Co-authors
- Syed Tanzeel RabaniAkib Mohi Ud Din KhandayNusrat RoufAli Shariq ImranMudasir Ahmad WaniZenun KastratiBharat BhushanRutvij H. Jhaveri
- Topics
- Misinformation and Its Impacts (7 papers)Sentiment Analysis and Opinion Mining (7 papers)Mental Health via Writing (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONESustainability
- Partner nations
- IndiaSaudi ArabiaCzechia
In The Last Decade
Qamar Rayees Khan
17 papers receiving 388 citations
Hit Papers
Peers
Comparison fields: 5 of 80
- Artificial Intelligence 218
- Radiology, Nuclear Medicine and Imaging 153
- Sociology and Political Science 68
- Information Systems 67
- Social Psychology 47
Countries citing papers authored by Qamar Rayees Khan
This map shows the geographic impact of Qamar Rayees Khan'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 Qamar Rayees Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qamar Rayees Khan more than expected).
Fields of papers citing papers by Qamar Rayees Khan
This network shows the impact of papers produced by Qamar Rayees Khan. 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 Qamar Rayees Khan. The network helps show where Qamar Rayees Khan may publish in the future.
Co-authorship network of co-authors of Qamar Rayees Khan
This figure shows the co-authorship network connecting the top 25 collaborators of Qamar Rayees Khan. A scholar is included among the top collaborators of Qamar Rayees Khan 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 Qamar Rayees Khan. Qamar Rayees Khan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 14 | |
| 3 | 22 | |
| 4 | 2 | |
| 5 | 9 | |
| 6 | 2 | |
| 7 | 34 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 5 | |
| 11 | 8 | |
| 12 | 46 | |
| 13 | 16 | |
| 14 | 4 | |
| 15 | Machine learning based approaches for detecting COVID-19 using clinical text databreakdown → | 213 |
| 16 | 25 | |
| 17 | 3 |
About Qamar Rayees Khan
Qamar Rayees Khan is a scholar working on Applied Psychology, Artificial Intelligence and Social Psychology, having authored 17 papers that have together received 411 indexed citations. Recurring topics across this work include Misinformation and Its Impacts (7 papers), Sentiment Analysis and Opinion Mining (7 papers) and Mental Health via Writing (5 papers). The work is most often cited by research in Health Information Management (45 citations), Health Informatics (13 citations) and Artificial Intelligence (218 citations). Qamar Rayees Khan has collaborated with scholars based in India, Saudi Arabia and Czechia. Frequent co-authors include Syed Tanzeel Rabani, Akib Mohi Ud Din Khanday, Nusrat Rouf, Ali Shariq Imran, Mudasir Ahmad Wani, Zenun Kastrati, Bharat Bhushan, Rutvij H. Jhaveri, Roshani Raut and Mohd Naseem. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Sustainability.
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.