De Huang
- Molecular Biology
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Computational Theory and Mathematics top 5%
- Control and Systems Engineering
- Co-authors
- Guang-Bin HuangYuan ChangWenzheng BaoZheng YinZhu‐Hong YouXiaobo ZhouKyungsook HanJiming Liu
- Topics
- Machine Learning in Bioinformatics (6 papers)Bioinformatics and Genomic Networks (4 papers)Protein Structure and Dynamics (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputational Theory and MathematicsArtificial Intelligence
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
De Huang
18 papers receiving 574 citations
Peers
Comparison fields: 5 of 90
- Molecular Biology 246
- Artificial Intelligence 173
- Computer Vision and Pattern Recognition 150
- Computational Theory and Mathematics 94
- Control and Systems Engineering 59
Countries citing papers authored by De Huang
This map shows the geographic impact of De Huang'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 De Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites De Huang more than expected).
Fields of papers citing papers by De Huang
This network shows the impact of papers produced by De Huang. 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 De Huang. The network helps show where De Huang may publish in the future.
Co-authorship network of co-authors of De Huang
This figure shows the co-authorship network connecting the top 25 collaborators of De Huang. A scholar is included among the top collaborators of De Huang 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 De Huang. De Huang 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 | 0 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 10 | |
| 6 | 1 | |
| 7 | 27 | |
| 8 | 5 | |
| 9 | 40 | |
| 10 | 29 | |
| 11 | 72 | |
| 12 | 12 | |
| 13 | 39 | |
| 14 | 11 | |
| 15 | The comparative study between ELM and SVM on predicting the postoperative survival time of NSCLC patients | 1 |
| 16 | 58 | |
| 17 | 6 | |
| 18 | 150 | |
| 19 | 112 | |
| 20 | 10 |
About De Huang
De Huang is a scholar working on Radiological and Ultrasound Technology, Media Technology and Safety, Risk, Reliability and Quality, having authored 20 papers that have together received 588 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (6 papers), Bioinformatics and Genomic Networks (4 papers) and Protein Structure and Dynamics (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (150 citations), Computational Theory and Mathematics (94 citations) and Artificial Intelligence (173 citations). De Huang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Guang-Bin Huang, Yuan Chang, Wenzheng Bao, Zheng Yin, Zhu‐Hong You, Xiaobo Zhou, Kyungsook Han, Jiming Liu, Yiu‐ming Cheung and Zhenhua Huang. Their work appears in journals such as Bioinformatics, International Journal of Hydrogen Energy and BMC Bioinformatics.
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.