Nusrat Jahan
- Plant Science
- Artificial Intelligence top 10%
- Analytical Chemistry top 10%
- Health Information Management top 5%
- Computer Vision and Pattern Recognition
- Co-authors
- Imran MahmudZakia SultanaPaulo FloresF. M. Javed Mehedi ShamratZarrin TasnimAndrew FriskopZhao ZhangThangarajah Akilan
- Topics
- Smart Agriculture and AI (8 papers)Artificial Intelligence in Healthcare (6 papers)Sentiment Analysis and Opinion Mining (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessFuel
- Partner nations
- BangladeshUnited StatesCanada
In The Last Decade
Nusrat Jahan
59 papers receiving 341 citations
Peers
Comparison fields: 5 of 112
- Plant Science 125
- Artificial Intelligence 95
- Analytical Chemistry 50
- Health Information Management 48
- Computer Vision and Pattern Recognition 37
Countries citing papers authored by Nusrat Jahan
This map shows the geographic impact of Nusrat Jahan'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 Nusrat Jahan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nusrat Jahan more than expected).
Fields of papers citing papers by Nusrat Jahan
This network shows the impact of papers produced by Nusrat Jahan. 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 Nusrat Jahan. The network helps show where Nusrat Jahan may publish in the future.
Co-authorship network of co-authors of Nusrat Jahan
This figure shows the co-authorship network connecting the top 25 collaborators of Nusrat Jahan. A scholar is included among the top collaborators of Nusrat Jahan 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 Nusrat Jahan. Nusrat Jahan 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 | 0 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 4 | |
| 11 | 7 | |
| 12 | 4 | |
| 13 | 3 | |
| 14 | 8 | |
| 15 | 19 | |
| 16 | 2 | |
| 17 | 4 | |
| 18 | 7 | |
| 19 | 13 | |
| 20 | Application Of K-Means Clustering Algorithm To Determine The Density Of Demand Of Different Kinds Of Jobs | 19 |
About Nusrat Jahan
Nusrat Jahan is a scholar working on Health Information Management, Artificial Intelligence and Medical Laboratory Technology, having authored 68 papers that have together received 357 indexed citations. Recurring topics across this work include Smart Agriculture and AI (8 papers), Artificial Intelligence in Healthcare (6 papers) and Sentiment Analysis and Opinion Mining (5 papers). The work is most often cited by research in Health Information Management (48 citations), Analytical Chemistry (50 citations) and Plant Science (125 citations). Nusrat Jahan has collaborated with scholars based in Bangladesh, United States and Canada. Frequent co-authors include Imran Mahmud, Zakia Sultana, Paulo Flores, F. M. Javed Mehedi Shamrat, Zarrin Tasnim, Andrew Friskop, Zhao Zhang, Thangarajah Akilan, Jane L. Harvill and Md. Sazzat Hossain Sarker. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Fuel.
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.