An Q Dinh
- Molecular Medicine top 2%
- Infectious Diseases top 10%
- Epidemiology
- Health Information Management top 1%
- Molecular Biology
- Co-authors
- Somya D. MohantyCésar A. AriasBlake HansonTruc T. TranWilliam R. MillerRafael RíosLorena DíazAyesha Khan
- Topics
- Antibiotic Resistance in Bacteria (18 papers)Antimicrobial Resistance in Staphylococcus (18 papers)Bacterial Identification and Susceptibility Testing (12 papers)
- Journals
- SHILAP Revista de lepidopterologíaClinical Infectious DiseasesScientific Reports
- Partner nations
- United StatesColombiaChile
In The Last Decade
An Q Dinh
37 papers receiving 776 citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Molecular Medicine 278
- Infectious Diseases 197
- Epidemiology 160
- Health Information Management 159
- Molecular Biology 141
Countries citing papers authored by An Q Dinh
This map shows the geographic impact of An Q Dinh'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 An Q Dinh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites An Q Dinh more than expected).
Fields of papers citing papers by An Q Dinh
This network shows the impact of papers produced by An Q Dinh. 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 An Q Dinh. The network helps show where An Q Dinh may publish in the future.
Co-authorship network of co-authors of An Q Dinh
This figure shows the co-authorship network connecting the top 25 collaborators of An Q Dinh. A scholar is included among the top collaborators of An Q Dinh 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 An Q Dinh. An Q Dinh 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 | 10 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 25 | |
| 7 | 3 | |
| 8 | 2 | |
| 9 | 0 | |
| 10 | 7 | |
| 11 | 38 | |
| 12 | 12 | |
| 13 | 40 | |
| 14 | 0 | |
| 15 | A data-driven approach to predicting diabetes and cardiovascular disease with machine learningbreakdown → | 275 |
| 16 | 45 | |
| 17 | 1 | |
| 18 | 4 | |
| 19 | 20 | |
| 20 | 39 |
About An Q Dinh
An Q Dinh is a scholar working on Molecular Medicine, Applied Microbiology and Biotechnology and Clinical Biochemistry, having authored 40 papers that have together received 797 indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (18 papers), Antimicrobial Resistance in Staphylococcus (18 papers) and Bacterial Identification and Susceptibility Testing (12 papers). The work is most often cited by research in Molecular Medicine (278 citations), Applied Microbiology and Biotechnology (92 citations) and Health Information Management (159 citations). An Q Dinh has collaborated with scholars based in United States, Colombia and Chile. Frequent co-authors include Somya D. Mohanty, César A. Arias, Blake Hanson, Truc T. Tran, William R. Miller, Rafael Ríos, Lorena Díaz, Ayesha Khan, Audrey Wanger and José M. Munita. Their work appears in journals such as SHILAP Revista de lepidopterología, Clinical Infectious Diseases and Scientific Reports.
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.