Md Tabrez Nafis
- Artificial Intelligence
- Health Information Management top 5%
- Information Systems
- Radiology, Nuclear Medicine and Imaging
- Cardiology and Cardiovascular Medicine
- Co-authors
- M. Afshar AlamMuhammad ArifGuojun WangRanjit BiswasHafiz Tayyab RaufSaleh AlbahliShahab Saquib SohailGautam Siddharth Kashyap
- Topics
- Artificial Intelligence in Healthcare (4 papers)Spam and Phishing Detection (3 papers)Advanced Text Analysis Techniques (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of Cleaner ProductionIEEE Access
- Partner nations
- IndiaSaudi ArabiaChina
In The Last Decade
Md Tabrez Nafis
21 papers receiving 196 citations
Peers
Comparison fields: 5 of 85
- Artificial Intelligence 90
- Health Information Management 50
- Information Systems 37
- Radiology, Nuclear Medicine and Imaging 34
- Cardiology and Cardiovascular Medicine 27
Countries citing papers authored by Md Tabrez Nafis
This map shows the geographic impact of Md Tabrez Nafis'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 Md Tabrez Nafis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Md Tabrez Nafis more than expected).
Fields of papers citing papers by Md Tabrez Nafis
This network shows the impact of papers produced by Md Tabrez Nafis. 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 Md Tabrez Nafis. The network helps show where Md Tabrez Nafis may publish in the future.
Co-authorship network of co-authors of Md Tabrez Nafis
This figure shows the co-authorship network connecting the top 25 collaborators of Md Tabrez Nafis. A scholar is included among the top collaborators of Md Tabrez Nafis 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 Md Tabrez Nafis. Md Tabrez Nafis 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 | 4 | |
| 3 | 23 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 3 | |
| 10 | 19 | |
| 11 | 2 | |
| 12 | 3 | |
| 13 | 2 | |
| 14 | 2 | |
| 15 | Internet Banking Fraud Detection Using Deep Learning Based on Decision Tree and Multilayer Perceptron | 5 |
| 16 | 1 | |
| 17 | 2 | |
| 18 | 6 | |
| 19 | 6 | |
| 20 | 0 |
About Md Tabrez Nafis
Md Tabrez Nafis is a scholar working on Health Informatics, Health Information Management and Artificial Intelligence, having authored 27 papers that have together received 214 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (4 papers), Spam and Phishing Detection (3 papers) and Advanced Text Analysis Techniques (3 papers). The work is most often cited by research in Health Information Management (50 citations), Health Informatics (9 citations) and Artificial Intelligence (90 citations). Md Tabrez Nafis has collaborated with scholars based in India, Saudi Arabia and China. Frequent co-authors include M. Afshar Alam, Muhammad Arif, Guojun Wang, Ranjit Biswas, Hafiz Tayyab Rauf, Muhammad Arif, Saleh Albahli, Shahab Saquib Sohail, Gautam Siddharth Kashyap and Mohd Abdul Ahad. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and IEEE Access.
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.