Hua Xu
- Molecular Biology top 1%
- Artificial Intelligence top 0.1%
- Health Information Management top 0.05%
- Computational Theory and Mathematics top 0.5%
- Epidemiology top 5%
- Topics
- Biomedical Text Mining and Ontologies (175 papers)Topic Modeling (108 papers)Natural Language Processing Techniques (65 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Hua Xu
370 papers receiving 8.9k citations
Hit Papers
Peers
Comparison fields: 5 of 205
- Molecular Biology 4.4k
- Artificial Intelligence 4.4k
- Health Information Management 1.0k
- Computational Theory and Mathematics 651
- Epidemiology 494
Countries citing papers authored by Hua Xu
This map shows the geographic impact of Hua Xu'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 Hua Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hua Xu more than expected).
Fields of papers citing papers by Hua Xu
This network shows the impact of papers produced by Hua Xu. 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 Hua Xu. The network helps show where Hua Xu may publish in the future.
Co-authorship network of co-authors of Hua Xu
This figure shows the co-authorship network connecting the top 25 collaborators of Hua Xu. A scholar is included among the top collaborators of Hua Xu 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 Hua Xu. Hua Xu 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 | 2 | |
| 3 | 4 | |
| 4 | 4 | |
| 5 | 4 | |
| 6 | 1 | |
| 7 | 26 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 7 | |
| 11 | 10 | |
| 12 | 6 | |
| 13 | 5 | |
| 14 | 15 | |
| 15 | 43 | |
| 16 | Conformance Assessment of PD-L1 Expression Between Primary Tumour and Nodal Metastases in Non-Small-Cell Lung Cancer | 2 |
| 17 | Anti-tumor effect of aloe-emodin on cervical cancer cells was associated with human papillomavirus E6/E7 and glucose metabolism | 1 |
| 18 | UTH_CCB System for Adverse Drug Reaction Extraction from Drug Labels at TAC-ADR 2017. | 14 |
| 19 | Quality of care metric reporting from clinical narratives: Assessing ontology components | 1 |
| 20 | 40 |
About Hua Xu
Hua Xu is a scholar working on Health Informatics, Health Information Management and Artificial Intelligence, having authored 399 papers that have together received 9.1k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (175 papers), Topic Modeling (108 papers) and Natural Language Processing Techniques (65 papers). The work is most often cited by research in Health Informatics (481 citations), Health Information Management (1.0k citations) and Artificial Intelligence (4.4k citations). Hua Xu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Yonghui Wu, Joshua C. Denny, Min Jiang, Yaoyun Zhang, Yukun Chen, Qiang Wei, Buzhou Tang, Jingchun Sun, Jingqi Wang and S. Trent Rosenbloom. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Lancet and Nucleic Acids Research.
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.