Xiaomei Han
Impact in
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- Cardiac electrophysiology and arrhythmias
- ECG Monitoring and Analysis
Papers in
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- Gut microbiota and health 2
- Machine Learning in Bioinformatics 1
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- Computational Drug Discovery Methods 3
- Co-authors
- David G. Strauss (5 shared papers)Caiyun Wu (1 shared paper)Min Wu (1 shared paper)Aaron Randolph (1 shared paper)Yuri A. Kuryshev (1 shared paper)Bradley J. Ridder (1 shared paper)Zhihua Li (1 shared paper)Gary R. Mirams (1 shared paper)
- Journals
- Clinical Pharmacology & Therapeutics (3 papers)BMC Bioinformatics (2 papers)Scientific Reports (1 paper)JAMA Network Open (1 paper)Clinical and Translational Science (1 paper)
- Partner nations
- United StatesChinaNetherlands
In The Last Decade
Xiaomei Han
12 papers receiving 183 citations
Peers
Comparison fields: 5 of 58
- Cardiology and Cardiovascular Medicine 102
- Health Informatics 3
- Anesthesiology and Pain Medicine 11
- Toxicology 6
- Computational Theory and Mathematics 25
Countries citing papers authored by Xiaomei Han
This map shows the geographic impact of Xiaomei Han'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 Xiaomei Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaomei Han more than expected).
Fields of papers citing papers by Xiaomei Han
This network shows the impact of papers produced by Xiaomei Han. 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 Xiaomei Han. The network helps show where Xiaomei Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaomei Han, 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 | 2018 | 114 | |
| 2 | 2022 | 34 | |
| 3 | 2017 | 10 | |
| 4 | 2021 | 9 | |
| 5 | 2023 | 8 | |
| 6 | 2024 | 4 | |
| 7 | 2024 | 2 | |
| 8 | 2023 | 2 | |
| 9 | [Study on the construction of bridge table of Chinese dietary exposure estimation model]. | 2008 | 2 |
| 10 | Study of Emergency Materials Scheduling Problem Baesd on ELS3 | 2009 | 1 |
| 11 | [Establishment of database for food classification and coding in Chinese dietary exposure assessment]. | 2010 | 1 |
| 12 | 2022 | 1 |
About Xiaomei Han
Xiaomei Han is a scholar working on Molecular Biology, Computational Theory and Mathematics, Infectious Diseases, Public Health, Environmental and Occupational Health and Emergency Medicine, having authored 12 papers that have together received 188 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (3 papers), Cardiac Arrest and Resuscitation (2 papers), Gut microbiota and health (2 papers), Cardiac electrophysiology and arrhythmias (1 paper), Machine Learning in Bioinformatics (1 paper), Safety and Risk Management (1 paper), Poisoning and overdose treatments (1 paper) and Water Treatment and Disinfection (1 paper). The work is most often cited by research in Cardiology and Cardiovascular Medicine (102 citations), Health Informatics (3 citations), Anesthesiology and Pain Medicine (11 citations), Toxicology (6 citations) and Computational Theory and Mathematics (25 citations). Xiaomei Han has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include David G. Strauss, Caiyun Wu, Min Wu, Aaron Randolph, Yuri A. Kuryshev, Bradley J. Ridder, Zhihua Li, Gary R. Mirams, Ross H. Johnstone and James Kramer. Their work appears in journals such as Clinical Pharmacology & Therapeutics, BMC Bioinformatics, Scientific Reports, JAMA Network Open and Clinical and Translational Science.
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.