Amber B. Tang

26 papers receiving 378 citations

Peers

Amber B. Tang
Comparison fields: 5 of 55
  • Virology 19
  • Cardiology and Cardiovascular Medicine 51
  • Modeling and Simulation 8
  • Infectious Diseases 36
  • Public Health, Environmental and Occupational Health 35
Replace Maria Giner‐Soriano with:
Maria Giner‐Soriano Spain
Zahra Heydarifard Iran
Edmond D Brewer United States
Sreshtha Chowdhury Bangladesh
Mebrahtu G. Tedla Ethiopia
Karam R. Motawea Egypt
Chathurani Sigera Sri Lanka
Sayem Borhan Canada
Matthew P. Driver United States
Mència Benítez Spain
Amber B. Tang relative to Maria Giner‐Soriano Spain Maria Giner‐Soriano's profile →
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Citations per year

Countries citing papers authored by Amber B. Tang

Since Specialization
Citations

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

Fields of papers citing papers by Amber B. Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amber B. Tang. 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 Amber B. Tang. The network helps show where Amber B. Tang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201759
2 201858
3 202236
4 202433
5 202021
6 201818
7 202317
8 202215
9 202415
10 201514
11 201711
12 202211
13 201910
14 202110
15 20239
16 20188
17
Selecting deep neural networks that yield consistent attribution-based interpretations for genomics.
20226
18 20256
19 20195
20 20235

About Amber B. Tang

Amber B. Tang is a scholar working on Cardiology and Cardiovascular Medicine, Infectious Diseases, Public Health, Environmental and Occupational Health, Psychiatry and Mental health and Health Information Management, having authored 28 papers that have together received 386 indexed citations. Recurring topics across this work include Heart Failure Treatment and Management (6 papers), Epilepsy research and treatment (2 papers), Obesity, Physical Activity, Diet (2 papers), Cardiac Arrhythmias and Treatments (2 papers), Opioid Use Disorder Treatment (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Healthcare Policy and Management (1 paper) and Pulmonary Hypertension Research and Treatments (1 paper). The work is most often cited by research in Virology (19 citations), Cardiology and Cardiovascular Medicine (51 citations), Modeling and Simulation (8 citations), Infectious Diseases (36 citations) and Public Health, Environmental and Occupational Health (35 citations). Amber B. Tang has collaborated with scholars based in United States and China. Frequent co-authors include Jan Medlock, Abhishek Pandey, Alison P. Galvani, Laura Skrip, Alyssa S. Parpia, Joseph E. Ebinger, Jiaojiao Zou, Lina Yang, Qian Lin and Gregg C. Fonarow. Their work appears in journals such as Circulation Heart Failure, International Journal of Environmental Research and Public Health, JAMA Cardiology, JAMA Network Open and Surgery.

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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