Hua Xu
- Health Informatics top 0.1%
- Health Information Management top 0.05%
- Electronic Health Records Systems 20
- Artificial Intelligence top 0.1%
- Topic Modeling 108
- Natural Language Processing Techniques 65
- Machine Learning in Healthcare 48
- Semantic Web and Ontologies 30
- Toxicology top 0.2%
- Molecular Biology top 1%
- Biomedical Text Mining and Ontologies 175
- Bioinformatics and Genomic Networks 27
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- Computational Drug Discovery Methods 30
- Journals
- Proceedings of the National Academy of Sciences (1 paper)The Lancet (2 papers)Nucleic Acids Research (1 paper)
- 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
- Health Informatics 481
- Health Information Management 1.0k
- Artificial Intelligence 4.4k
- Toxicology 358
- Molecular Biology 4.4k
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
The 25 scholars most cited alongside Hua Xu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 26 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 0 | |
| 10 | 2024 | 7 | |
| 11 | 2023 | 10 | |
| 12 | 2023 | 6 | |
| 13 | 2022 | 5 | |
| 14 | 2022 | 15 | |
| 15 | 2020 | 43 | |
| 16 | Conformance Assessment of PD-L1 Expression Between Primary Tumour and Nodal Metastases in Non-Small-Cell Lung Cancer | 2019 | 2 |
| 17 | Anti-tumor effect of aloe-emodin on cervical cancer cells was associated with human papillomavirus E6/E7 and glucose metabolism | 2019 | 1 |
| 18 | UTH_CCB System for Adverse Drug Reaction Extraction from Drug Labels at TAC-ADR 2017. | 2017 | 14 |
| 19 | Quality of care metric reporting from clinical narratives: Assessing ontology components | 2014 | 1 |
| 20 | 2013 | 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), Natural Language Processing Techniques (65 papers), Machine Learning in Healthcare (48 papers), Computational Drug Discovery Methods (30 papers), Semantic Web and Ontologies (30 papers), Bioinformatics and Genomic Networks (27 papers) and Electronic Health Records Systems (20 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.