Khandaker Mohammad Mohi Uddin
- Artificial Intelligence top 5%
- Health Information Management top 1%
- Radiology, Nuclear Medicine and Imaging
- Neurology
- Computer Vision and Pattern Recognition
- Co-authors
- Samrat Kumar DeyRafid MostafizMd. Ashraf UddinSunil AryalHafiz Md. Hasan BabuMd Mahbubur RahmanUmme Raihan SiddiqiBikash Kumar Paul
- Topics
- Artificial Intelligence in Healthcare (14 papers)AI in cancer detection (14 papers)Radiomics and Machine Learning in Medical Imaging (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- BangladeshAustraliaUnited States
In The Last Decade
Khandaker Mohammad Mohi Uddin
38 papers receiving 429 citations
Peers
Comparison fields: 5 of 87
- Artificial Intelligence 217
- Health Information Management 142
- Radiology, Nuclear Medicine and Imaging 87
- Neurology 60
- Computer Vision and Pattern Recognition 44
Countries citing papers authored by Khandaker Mohammad Mohi Uddin
This map shows the geographic impact of Khandaker Mohammad Mohi Uddin'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 Khandaker Mohammad Mohi Uddin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Khandaker Mohammad Mohi Uddin more than expected).
Fields of papers citing papers by Khandaker Mohammad Mohi Uddin
This network shows the impact of papers produced by Khandaker Mohammad Mohi Uddin. 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 Khandaker Mohammad Mohi Uddin. The network helps show where Khandaker Mohammad Mohi Uddin may publish in the future.
Co-authorship network of co-authors of Khandaker Mohammad Mohi Uddin
This figure shows the co-authorship network connecting the top 25 collaborators of Khandaker Mohammad Mohi Uddin. A scholar is included among the top collaborators of Khandaker Mohammad Mohi Uddin 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 Khandaker Mohammad Mohi Uddin. Khandaker Mohammad Mohi Uddin 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 | 3 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 4 | |
| 9 | 12 | |
| 10 | 6 | |
| 11 | 5 | |
| 12 | 26 | |
| 13 | 1 | |
| 14 | 12 | |
| 15 | 8 | |
| 16 | 4 | |
| 17 | 6 | |
| 18 | 34 | |
| 19 | 6 | |
| 20 | 2 |
About Khandaker Mohammad Mohi Uddin
Khandaker Mohammad Mohi Uddin is a scholar working on Health Information Management, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 48 papers that have together received 446 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (14 papers), AI in cancer detection (14 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). The work is most often cited by research in Health Information Management (142 citations), Neurology (60 citations) and Artificial Intelligence (217 citations). Khandaker Mohammad Mohi Uddin has collaborated with scholars based in Bangladesh, Australia and United States. Frequent co-authors include Samrat Kumar Dey, Rafid Mostafiz, Md. Ashraf Uddin, Sunil Aryal, Hafiz Md. Hasan Babu, Md Mahbubur Rahman, Umme Raihan Siddiqi, Bikash Kumar Paul, Mohammad Shorif Uddin and Md. Saikat Islam Khan. 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.