Chunhua Weng
- Artificial Intelligence top 0.5%
- Molecular Biology top 5%
- Health Information Management top 0.02%
- Public Health, Environmental and Occupational Health top 1%
- Management Science and Operations Research top 0.5%
- Co-authors
- Nicole G. WeiskopfGeorge HripcsakAlexander RusanovRiccardo MiottoPatrick RyanMary Regina BolandJohn H. GennariMichael G. Kahn
- Topics
- Biomedical Text Mining and Ontologies (123 papers)Topic Modeling (55 papers)Machine Learning in Healthcare (53 papers)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Chunhua Weng
266 papers receiving 6.0k citations
Hit Papers
Peers
Comparison fields: 5 of 177
- Artificial Intelligence 2.2k
- Molecular Biology 1.9k
- Health Information Management 1.5k
- Public Health, Environmental and Occupational Health 1.1k
- Management Science and Operations Research 682
Countries citing papers authored by Chunhua Weng
This map shows the geographic impact of Chunhua Weng'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 Chunhua Weng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chunhua Weng more than expected).
Fields of papers citing papers by Chunhua Weng
This network shows the impact of papers produced by Chunhua Weng. 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 Chunhua Weng. The network helps show where Chunhua Weng may publish in the future.
Co-authorship network of co-authors of Chunhua Weng
This figure shows the co-authorship network connecting the top 25 collaborators of Chunhua Weng. A scholar is included among the top collaborators of Chunhua Weng 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 Chunhua Weng. Chunhua Weng 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 | 0 | |
| 3 | 17 | |
| 4 | 11 | |
| 5 | 17 | |
| 6 | 3 | |
| 7 | 0 | |
| 8 | 15 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 23 | |
| 12 | 0 | |
| 13 | 28 | |
| 14 | 2 | |
| 15 | 9 | |
| 16 | 6 | |
| 17 | 34 | |
| 18 | 10 | |
| 19 | 6 | |
| 20 | Desiderata for Major Eligibility Criteria in Breast Cancer Clinical Trials. | 2 |
About Chunhua Weng
Chunhua Weng is a scholar working on Health Information Management, Health Informatics and Artificial Intelligence, having authored 284 papers that have together received 6.1k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (123 papers), Topic Modeling (55 papers) and Machine Learning in Healthcare (53 papers). The work is most often cited by research in Health Information Management (1.5k citations), Health Informatics (438 citations) and Artificial Intelligence (2.2k citations). Chunhua Weng has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Nicole G. Weiskopf, George Hripcsak, Alexander Rusanov, Riccardo Miotto, Patrick Ryan, Mary Regina Boland, John H. Gennari, Michael G. Kahn, Gunnar Hartvigsen and Taxiarchis Botsis. Their work appears in journals such as Nucleic Acids Research, Nature Communications and Nature Genetics.
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.