Samiya Khan
Impact in
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- Big Data and Business Intelligence
- Information Systems top 10%
- Cloud Computing and Resource Management
- Blockchain Technology Applications and Security
Papers in
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- Cloud Computing and Resource Management 4
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- IoT and Edge/Fog Computing 4
- Co-authors
- Mansaf Alam (9 shared papers)Kashish Ara Shakil (5 shared papers)Xiufeng Liu (2 shared papers)Arleen D. Auerbach (1 shared paper)Daniel J. Weisdorf (1 shared paper)Stella M. Davies (1 shared paper)JE Wagner (1 shared paper)Mahmoud Elkhodr (2 shared papers)
- Journals
- Multimedia Tools and Applications (1 paper)Electronics (1 paper)Information Processing & Management (1 paper)Future Internet (1 paper)Digital Health (1 paper)
- Partner nations
- IndiaUnited KingdomSaudi Arabia
In The Last Decade
Samiya Khan
14 papers receiving 184 citations
Peers
Comparison fields: 5 of 68
- Management Information Systems 33
- Information Systems 66
- Computer Science Applications 14
- Health Informatics 3
- Hematology 21
Countries citing papers authored by Samiya Khan
This map shows the geographic impact of Samiya 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 Samiya Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samiya Khan more than expected).
Fields of papers citing papers by Samiya Khan
This network shows the impact of papers produced by Samiya 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 Samiya Khan. The network helps show where Samiya Khan may publish in the future.
Co-authors
The 22 scholars most cited alongside Samiya Khan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 81 | |
| 2 | Unrelated donor bone marrow transplantation for Fanconi anemia. | 1996 | 35 |
| 3 | 2020 | 12 | |
| 4 | 2023 | 11 | |
| 5 | 2019 | 7 | |
| 6 | 2024 | 7 | |
| 7 | 2020 | 6 | |
| 8 | 2024 | 5 | |
| 9 | 2016 | 5 | |
| 10 | 2019 | 5 | |
| 11 | 2021 | 3 | |
| 12 | 2022 | 3 | |
| 13 | 2023 | 3 | |
| 14 | 2018 | 3 | |
| 15 | 2024 | 0 | |
| 16 | 2023 | 0 | |
| 17 | 2022 | 0 | |
| 18 | 2022 | 0 | |
| 19 | 2024 | 0 | |
| 20 | Dyslipidemia in the metabolic syndrome: clinical implications and management. | 2006 | 0 |
About Samiya Khan
Samiya Khan is a scholar working on Information Systems, Computer Networks and Communications, Management Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 186 indexed citations. Recurring topics across this work include Big Data and Business Intelligence (5 papers), Cloud Computing and Resource Management (4 papers), IoT and Edge/Fog Computing (4 papers), Data Quality and Management (2 papers), Topic Modeling (2 papers), Online Learning and Analytics (2 papers), DNA Repair Mechanisms (1 paper) and Advanced X-ray and CT Imaging (1 paper). The work is most often cited by research in Management Information Systems (33 citations), Information Systems (66 citations), Computer Science Applications (14 citations), Health Informatics (3 citations) and Hematology (21 citations). Samiya Khan has collaborated with scholars based in India, United Kingdom and Saudi Arabia. Frequent co-authors include Mansaf Alam, Kashish Ara Shakil, Xiufeng Liu, Arleen D. Auerbach, Daniel J. Weisdorf, Stella M. Davies, JE Wagner, Mahmoud Elkhodr, Sonali Vyas and Deepshikha Bhargava. Their work appears in journals such as Multimedia Tools and Applications, Electronics, Information Processing & Management, Future Internet and Digital Health.
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.