Kevin Lu

2.7k citations
118 papers · 1.6k · h-index 20

Impact in

Papers in

Kevin Lu

112 papers receiving 1.6k citations

Peers

Kevin Lu
Comparison fields: 5 of 143
  • Modeling and Simulation 139
  • Family Practice 33
  • Infectious Diseases 289
  • Geriatrics and Gerontology 32
  • Health 64
Replace Thomas J. Papadimos with:
Thomas J. Papadimos United States
Jennifer Abbasi United States
Hassan Alwafi Saudi Arabia
Mina Tadrous Canada
Farida Ahmad United States
Saurav Basu India
Farid Najafi Iran
Georgia Kourlaba Greece
Stanley Xu United States
Joshua M. Sharfstein United States
Kevin Lu relative to Thomas J. Papadimos United States Thomas J. Papadimos's profile →
Citations per field
00.5×1.5×1.9×
Thomas J. Papadimos · 1×
Citations per year

Countries citing papers authored by Kevin Lu

Since Specialization
Citations

This map shows the geographic impact of Kevin Lu'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 Kevin Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Lu more than expected).

Fields of papers citing papers by Kevin Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin Lu. 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 Kevin Lu. The network helps show where Kevin Lu may publish in the future.

Co-authors

The 25 scholars most cited alongside Kevin Lu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kevin Lu Line = papers co-authored together Kevin Lu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 118 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020223
2 2012122
3 2006119
4 202172
5 201569
6 201366
7 201455
8 202152
9 202149
10 201639
11 202132
12 202230
13 201430
14 200626
15 201623
16 201823
17 201822
18 201521
19 201620
20 201219

About Kevin Lu

Kevin Lu is a scholar working on Economics and Econometrics, Epidemiology, Infectious Diseases, Geriatrics and Gerontology and Psychiatry and Mental health, having authored 118 papers that have together received 1.6k indexed citations. Recurring topics across this work include Pharmaceutical Practices and Patient Outcomes (11 papers), Health Systems, Economic Evaluations, Quality of Life (9 papers), Medication Adherence and Compliance (8 papers), Dementia and Cognitive Impairment Research (6 papers), Mobile Health and mHealth Applications (4 papers), Migraine and Headache Studies (4 papers), Pharmaceutical Economics and Policy (4 papers) and HIV/AIDS Research and Interventions (4 papers). The work is most often cited by research in Modeling and Simulation (139 citations), Family Practice (33 citations), Infectious Diseases (289 citations), Geriatrics and Gerontology (32 citations) and Health (64 citations). Kevin Lu has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Jing Yuan, Gang Lv, Minghui Li, Minghui Li, Jun Wu, Xiaomo Xiong, Ronald Tamler, Andrew P. Demidowich, Zachary T. Bloomgarden and Bin Jiang. Their work appears in journals such as Frontiers in Pharmacology, Value in Health, BMJ Open, AIDS Care and JAMA Network Open.

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.

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