Rafid Mostafiz
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Health Information Management top 5%
- Endocrinology, Diabetes and Metabolism
- Co-authors
- Mohammad Shorif UddinMohammad Motiur RahmanKhandaker Mohammad Mohi UddinMd. Mahfuz RezaBikash Kumar PaulSamrat Kumar DeyImran HossainMohammad M. Rahman
- Topics
- AI in cancer detection (7 papers)Radiomics and Machine Learning in Medical Imaging (5 papers)COVID-19 diagnosis using AI (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- BangladeshUnited StatesAustralia
In The Last Decade
Rafid Mostafiz
25 papers receiving 311 citations
Peers
Comparison fields: 5 of 68
- Artificial Intelligence 150
- Radiology, Nuclear Medicine and Imaging 112
- Computer Vision and Pattern Recognition 90
- Health Information Management 43
- Endocrinology, Diabetes and Metabolism 37
Countries citing papers authored by Rafid Mostafiz
This map shows the geographic impact of Rafid Mostafiz'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 Rafid Mostafiz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rafid Mostafiz more than expected).
Fields of papers citing papers by Rafid Mostafiz
This network shows the impact of papers produced by Rafid Mostafiz. 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 Rafid Mostafiz. The network helps show where Rafid Mostafiz may publish in the future.
Co-authorship network of co-authors of Rafid Mostafiz
This figure shows the co-authorship network connecting the top 25 collaborators of Rafid Mostafiz. A scholar is included among the top collaborators of Rafid Mostafiz 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 Rafid Mostafiz. Rafid Mostafiz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 6 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 0 | |
| 9 | 20 | |
| 10 | 17 | |
| 11 | 17 | |
| 12 | 20 | |
| 13 | 15 | |
| 14 | 6 | |
| 15 | 6 | |
| 16 | 61 | |
| 17 | 18 | |
| 18 | 2 | |
| 19 | 5 | |
| 20 | Speckle Noise Reduction for 3-D Ultrasound Images by Optimum Threshold Parameter Estimation of Wavelet Coefficients Using Fisher Discriminant Analysis | 2 |
About Rafid Mostafiz
Rafid Mostafiz is a scholar working on Computer Vision and Pattern Recognition, Health Information Management and Artificial Intelligence, having authored 29 papers that have together received 315 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Health Information Management (43 citations), Health Informatics (11 citations) and Radiology, Nuclear Medicine and Imaging (112 citations). Rafid Mostafiz has collaborated with scholars based in Bangladesh, United States and Australia. Frequent co-authors include Mohammad Shorif Uddin, Mohammad Motiur Rahman, Khandaker Mohammad Mohi Uddin, Md. Mahfuz Reza, Bikash Kumar Paul, Samrat Kumar Dey, Imran Hossain, Mohammad M. Rahman, Md. Mahmodul Hasan and Md. Ariful Islam. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.