William E. Yang

23 papers receiving 760 citations

Peers

William E. Yang
Comparison fields: 5 of 82
  • Health Informatics 24
  • General Health Professions 176
  • Oncology 160
  • Cardiology and Cardiovascular Medicine 127
  • Health Information Management 29
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Katherine Kolor United States
Anthony M. Proietto Australia
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Keerthi Gogineni United States
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Citations per year

Countries citing papers authored by William E. Yang

Since Specialization
Citations

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

Fields of papers citing papers by William E. Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William E. Yang. 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 William E. Yang. The network helps show where William E. Yang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001235
2 2020129
3 202169
4 202167
5 199942
6 201940
7 202133
8 201924
9 202124
10 199722
11 202416
12 201915
13 202115
14 201614
15 20208
16 20186
17 20196
18 20185
19
Impact of Innovation Initiatives in a Federal Government Agency: Measuring and Understanding the Influence of Culture and Employee Attitudes
20172
20 20172

About William E. Yang

William E. Yang is a scholar working on General Health Professions, Oncology, Cardiology and Cardiovascular Medicine, Molecular Biology and General Social Sciences, having authored 24 papers that have together received 777 indexed citations. Recurring topics across this work include Mobile Health and mHealth Applications (9 papers), Cancer-related Molecular Pathways (3 papers), Cell death mechanisms and regulation (2 papers), Antiplatelet Therapy and Cardiovascular Diseases (2 papers), HIV, Drug Use, Sexual Risk (1 paper), Biomedical Text Mining and Ontologies (1 paper), HIV/AIDS Research and Interventions (1 paper) and Genomics and Chromatin Dynamics (1 paper). The work is most often cited by research in Health Informatics (24 citations), General Health Professions (176 citations), Oncology (160 citations), Cardiology and Cardiovascular Medicine (127 citations) and Health Information Management (29 citations). William E. Yang has collaborated with scholars based in United States, China and Greece. Frequent co-authors include Gail E. Sonenshein, Min Wu, Jian Gang Shen, Mark J. Fitzgerald, Zalman Suldan, Raphaëlle Romieu, Dong Won Kim, Stefania Pianetti, Leonard P. Freedman and Marcello Arsura. Their work appears in journals such as JMIR mhealth and uhealth, Circulation Cardiovascular Quality and Outcomes, Current topics in microbiology and immunology, Molecular Cancer Therapeutics and Journal of the American College of Cardiology.

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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