Ming Dong
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 10%
- Signal Processing top 10%
- Computational Theory and Mathematics top 10%
- Co-authors
- Rohit KothariLijun WangManjeet RegeRavi KothariFarshad FotouhiYanhua ChenChuanling QiaoChao Yang
- Topics
- Advanced Clustering Algorithms Research (4 papers)Machine Learning in Healthcare (4 papers)Bayesian Methods and Mixture Models (3 papers)
- Journals
- IEEE Transactions on Biomedical EngineeringPattern RecognitionBiotechnology and Bioengineering
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Ming Dong
36 papers receiving 467 citations
Peers
Comparison fields: 5 of 98
- Artificial Intelligence 275
- Computer Vision and Pattern Recognition 144
- Information Systems 73
- Signal Processing 48
- Computational Theory and Mathematics 46
Countries citing papers authored by Ming Dong
This map shows the geographic impact of Ming Dong'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 Ming Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Dong more than expected).
Fields of papers citing papers by Ming Dong
This network shows the impact of papers produced by Ming Dong. 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 Ming Dong. The network helps show where Ming Dong may publish in the future.
Co-authorship network of co-authors of Ming Dong
This figure shows the co-authorship network connecting the top 25 collaborators of Ming Dong. A scholar is included among the top collaborators of Ming Dong 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 Ming Dong. Ming Dong 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 | 1 | |
| 4 | 9 | |
| 5 | 1 | |
| 6 | 9 | |
| 7 | Predicting the Outcome of Patient-Provider Communication Sequences using Recurrent Neural Networks and Probabilistic Models. | 7 |
| 8 | 7 | |
| 9 | Hidden Semi-Markov Model-Based Reputation Management System for Online to Offline (O2O) E-Commerce Markets | 4 |
| 10 | 20 | |
| 11 | 30 | |
| 12 | 52 | |
| 13 | 19 | |
| 14 | 44 | |
| 15 | 1 | |
| 16 | Can Fuzzy Logic Make Technical Analysis 20/20? | 4 |
| 17 | Language engineering for the Semantic Web: a digital library for endangered languages. | 6 |
| 18 | 3 | |
| 19 | 50 | |
| 20 | Exploring the Fuzzy Nature of Technical Patterns of U.S. Market. | 1 |
About Ming Dong
Ming Dong is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Health Information Management, having authored 38 papers that have together received 494 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (4 papers), Machine Learning in Healthcare (4 papers) and Bayesian Methods and Mixture Models (3 papers). The work is most often cited by research in Artificial Intelligence (275 citations), Computer Vision and Pattern Recognition (144 citations) and Signal Processing (48 citations). Ming Dong has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Rohit Kothari, Lijun Wang, Manjeet Rege, Ravi Kothari, Farshad Fotouhi, Yanhua Chen, Chuanling Qiao, Chao Yang, Hamid Soltanian‐Zadeh and Mostafa Ghannad‐Rezaie. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, Pattern Recognition and Biotechnology and Bioengineering.
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.