Mohammed Nazim Uddin
- Artificial Intelligence top 10%
- Information Systems top 10%
- Computer Vision and Pattern Recognition top 10%
- Plant Science
- Neurology
- Co-authors
- Seung-Bo ParkYeong Min JangMohammad Arif HossainSohrab HossainGeun‐Sik JoS. M. Riazul IslamKyung Sup KwakTrong Hai Duong
- Topics
- Artificial Intelligence in Healthcare (6 papers)Recommender Systems and Techniques (6 papers)Image Retrieval and Classification Techniques (4 papers)
- Partner nations
- BangladeshSouth KoreaUnited States
In The Last Decade
Mohammed Nazim Uddin
35 papers receiving 308 citations
Peers
Comparison fields: 5 of 99
- Artificial Intelligence 118
- Information Systems 76
- Computer Vision and Pattern Recognition 60
- Plant Science 40
- Neurology 33
Countries citing papers authored by Mohammed Nazim Uddin
This map shows the geographic impact of Mohammed Nazim 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 Mohammed Nazim Uddin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammed Nazim Uddin more than expected).
Fields of papers citing papers by Mohammed Nazim Uddin
This network shows the impact of papers produced by Mohammed Nazim 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 Mohammed Nazim Uddin. The network helps show where Mohammed Nazim Uddin may publish in the future.
Co-authorship network of co-authors of Mohammed Nazim Uddin
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammed Nazim Uddin. A scholar is included among the top collaborators of Mohammed Nazim 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 Mohammed Nazim Uddin. Mohammed Nazim 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 | 0 | |
| 2 | 5 | |
| 3 | 0 | |
| 4 | 11 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 18 | |
| 10 | 1 | |
| 11 | 11 | |
| 12 | 6 | |
| 13 | 3 | |
| 14 | 3 | |
| 15 | 23 | |
| 16 | 1 | |
| 17 | 3 | |
| 18 | 20 | |
| 19 | 7 | |
| 20 | 7 |
About Mohammed Nazim Uddin
Mohammed Nazim Uddin is a scholar working on Health Information Management, Health Informatics and Computer Vision and Pattern Recognition, having authored 40 papers that have together received 331 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (6 papers), Recommender Systems and Techniques (6 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in Health Information Management (23 citations), Neurology (33 citations) and Health Informatics (5 citations). Mohammed Nazim Uddin has collaborated with scholars based in Bangladesh, South Korea and United States. Frequent co-authors include Seung-Bo Park, Yeong Min Jang, Mohammad Arif Hossain, Sohrab Hossain, Geun‐Sik Jo, S. M. Riazul Islam, Kyung Sup Kwak, Trong Hai Duong, Ngoc Thanh Nguyên and Geun Sik Jo. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Diagnostics.
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.