Shih‐Jen Hwang
- Cardiology and Cardiovascular Medicine top 0.5%
- Endocrinology, Diabetes and Metabolism top 1%
- Epidemiology top 2%
- Nephrology top 0.5%
- Surgery top 5%
- Co-authors
- Daniel LevyCaroline S. FoxMartin G. LarsonRamachandran S. VasanEmelia J. BenjaminJoseph A. VitaMichael J. PencinaGary F. Mitchell
- Topics
- Chronic Kidney Disease and Diabetes (22 papers)Blood Pressure and Hypertension Studies (15 papers)Genetic Associations and Epidemiology (13 papers)
- Partner nations
- United StatesCanadaFrance
In The Last Decade
Shih‐Jen Hwang
102 papers receiving 6.3k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Cardiology and Cardiovascular Medicine 3.1k
- Endocrinology, Diabetes and Metabolism 1.1k
- Epidemiology 1.0k
- Nephrology 995
- Surgery 871
Countries citing papers authored by Shih‐Jen Hwang
This map shows the geographic impact of Shih‐Jen Hwang'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 Shih‐Jen Hwang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shih‐Jen Hwang more than expected).
Fields of papers citing papers by Shih‐Jen Hwang
This network shows the impact of papers produced by Shih‐Jen Hwang. 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 Shih‐Jen Hwang. The network helps show where Shih‐Jen Hwang may publish in the future.
Co-authorship network of co-authors of Shih‐Jen Hwang
This figure shows the co-authorship network connecting the top 25 collaborators of Shih‐Jen Hwang. A scholar is included among the top collaborators of Shih‐Jen Hwang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shih‐Jen Hwang. Shih‐Jen Hwang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 18 | |
| 6 | 1 | |
| 7 | 37 | |
| 8 | Abstract 18806: Integrated Proteomic Analysis of Cardiovascular Disease Reveals Novel Protein Quantitative Trait Loci | 1 |
| 9 | Abstract 19305: Higher Levels of Beta-2 Microglobulin Predict Incident Hypertension | 1 |
| 10 | 13 | |
| 11 | 40 | |
| 12 | 64 | |
| 13 | 127 | |
| 14 | 20 | |
| 15 | 20 | |
| 16 | 72 | |
| 17 | Abstract 17245: The Heritability of Ideal Cardiovascular Health: The Framingham Heart Study | 4 |
| 18 | 66 | |
| 19 | 93 | |
| 20 | 17 |
About Shih‐Jen Hwang
Shih‐Jen Hwang is a scholar working on Nephrology, Cardiology and Cardiovascular Medicine and Internal Medicine, having authored 102 papers that have together received 6.4k indexed citations. Recurring topics across this work include Chronic Kidney Disease and Diabetes (22 papers), Blood Pressure and Hypertension Studies (15 papers) and Genetic Associations and Epidemiology (13 papers). The work is most often cited by research in Nephrology (995 citations), Cardiology and Cardiovascular Medicine (3.1k citations) and Endocrinology, Diabetes and Metabolism (1.1k citations). Shih‐Jen Hwang has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Daniel Levy, Caroline S. Fox, Martin G. Larson, Ramachandran S. Vasan, Emelia J. Benjamin, Joseph A. Vita, Michael J. Pencina, Gary F. Mitchell, Naomi M. Hamburg and Joseph M. Massaro. Their work appears in journals such as Circulation, Gastroenterology 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.