Fei Wan

79 papers receiving 2.2k citations

Fei Wan's Hit Papers

A Randomized, Controlled Trial of Financial Incentives for Smoking Cessation 2009 · 602 citations
6020+5+11Years since publication200400600

Peers

Fei Wan
Comparison fields: 5 of 149
  • Applied Psychology 203
  • General Decision Sciences 46
  • Health 200
  • General Health Professions 484
  • Family Practice 42
Replace Kathryn A. Phillips with:
Kathryn A. Phillips United States
Benjamin M. Craig United States
Marilyn M. Schapira United States
Sarah T. Hawley United States
Andrew N. Freedman United States
Robert F. Nease United States
Kathryn E. Flynn United States
Deb Feldman‐Stewart Canada
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Elissa M. Ozanne United States
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Citations per field
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Kathryn A. Phillips · 1×
Citations per year

Countries citing papers authored by Fei Wan

Since Specialization
Citations

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

Fields of papers citing papers by Fei Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Fei Wan, 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 Fei Wan Line = papers co-authored together Fei Wan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 86 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Randomized, Controlled Trial of Financial Incentives for Smoking Cessation
Hit paper breakdown →
2009602
2 2006211
3 2013133
4 2013121
5 2009117
6 201183
7 201065
8 201060
9 200759
10 201358
11 201551
12 202443
13 202143
14 201541
15 202036
16 201836
17 201335
18 201531
19 201630
20 201828

About Fei Wan

Fei Wan is a scholar working on Oncology, Statistics and Probability, General Health Professions, Surgery and Pulmonary and Respiratory Medicine, having authored 86 papers that have together received 2.3k indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (13 papers), Statistical Methods and Inference (9 papers), Lymphoma Diagnosis and Treatment (8 papers), Health Literacy and Information Accessibility (6 papers), Statistical Methods and Bayesian Inference (6 papers), Health Systems, Economic Evaluations, Quality of Life (5 papers), CAR-T cell therapy research (5 papers) and Mobile Health and mHealth Applications (5 papers). The work is most often cited by research in Applied Psychology (203 citations), General Decision Sciences (46 citations), Health (200 citations), General Health Professions (484 citations) and Family Practice (42 citations). Fei Wan has collaborated with scholars based in United States, China and Colombia. Frequent co-authors include Nandita Mitra, David A. Asch, Henry A. Glick, Robert Galvin, Janet Audrain‐McGovern, Janet Weiner, Elizabeth L. Corbett, Mark V. Pauly, Kevin G. Volpp and Jingsan Zhu. Their work appears in journals such as Blood, Statistics in Medicine, BMC Medical Research Methodology, Biology of Blood and Marrow Transplantation and Journal of Surgical Oncology.

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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