Daya Yang

48 papers receiving 781 citations

Peers

Daya Yang
Comparison fields: 5 of 110
  • Nephrology 65
  • Endocrinology, Diabetes and Metabolism 127
  • Modeling and Simulation 35
  • Infectious Diseases 137
  • Cardiology and Cardiovascular Medicine 140
Replace Radosław Owczuk with:
Radosław Owczuk Poland
Izza Shahid United States
Carlen Reyes Spain
Danyong Liu China
Magdalena Wujtewicz Poland
Raden Ayu Tuty Kuswardhani Indonesia
Juan Sanchís Spain
Garima Arora United States
Alireza Hamidian Jahromi United States
Huiling Liang China
Daya Yang relative to Radosław Owczuk Poland Radosław Owczuk's profile →
Citations per field
00.5×3.9×
Radosław Owczuk · 1×
Citations per year

Countries citing papers authored by Daya Yang

Since Specialization
Citations

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

Fields of papers citing papers by Daya Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020181
2 2017126
3 2020102
4 202031
5 202230
6 201826
7 201522
8 202019
9 201219
10 201019
11 201419
12 201817
13 201915
14 202115
15 201914
16 201313
17 201311
18 201910
19 20129
20 20178

About Daya Yang

Daya Yang is a scholar working on Cardiology and Cardiovascular Medicine, Family Practice, Anesthesiology and Pain Medicine, Endocrinology, Diabetes and Metabolism and Internal Medicine, having authored 50 papers that have together received 807 indexed citations. Recurring topics across this work include Innovations in Medical Education (7 papers), Diabetes Management and Research (5 papers), Diabetes Treatment and Management (5 papers), Antiplatelet Therapy and Cardiovascular Diseases (4 papers), Heart Rate Variability and Autonomic Control (4 papers), Interprofessional Education and Collaboration (4 papers), Pain Management and Treatment (4 papers) and Cardiac Imaging and Diagnostics (3 papers). The work is most often cited by research in Nephrology (65 citations), Endocrinology, Diabetes and Metabolism (127 citations), Modeling and Simulation (35 citations), Infectious Diseases (137 citations) and Cardiology and Cardiovascular Medicine (140 citations). Daya Yang has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Xinxue Liao, Haipeng Xiao, Xiaodong Zhuang, Zhimin Du, Yue Leon Guo, Guifu Wu, Ming Kuang, Lichun Wang, Xun Hu and Han Xiao. Their work appears in journals such as Medical Teacher, International Journal of Cardiology, Cardiovascular Diabetology, Journal of the American College of Cardiology and European Journal of Preventive 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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