Ken Williams
- Endocrinology, Diabetes and Metabolism top 0.05%
- Diabetes, Cardiovascular Risks, and Lipoproteins 52
- Diabetes Management and Research 9
- Epidemiology top 0.5%
- Liver Disease Diagnosis and Treatment 13
- Adipokines, Inflammation, and Metabolic Diseases 11
- Rheumatology top 0.5%
- Physiology top 1%
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- Lipoproteins and Cardiovascular Health 25
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- Health Systems, Economic Evaluations, Quality of Life 10
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- Obesity, Physical Activity, Diet 7
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- Metabolism, Diabetes, and Cancer 7
- Co-authors
- Michael P. SternSteven M. HaffnerKelly J. HuntRalph B. D’AgostinoCarlos LorenzoAnthony J. HanleyAllan D. SnidermanInmaculada del Rincón
- Partner nations
- United StatesCanadaMexico
In The Last Decade
Ken Williams
95 papers receiving 11.8k citations
Hit Papers
Peers
Comparison fields: 5 of 169
- Endocrinology, Diabetes and Metabolism 6.3k
- Cardiology and Cardiovascular Medicine 2.3k
- Epidemiology 3.2k
- Rheumatology 1.2k
- Physiology 1.6k
Countries citing papers authored by Ken Williams
This map shows the geographic impact of Ken Williams'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 Ken Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken Williams more than expected).
Fields of papers citing papers by Ken Williams
This network shows the impact of papers produced by Ken Williams. 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 Ken Williams. The network helps show where Ken Williams may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ken Williams, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 4 | |
| 2 | 2014 | 94 | |
| 3 | Application of New Cholesterol Guidelines to a Population-Based Samplebreakdown → | 2014 | 467 |
| 4 | 2012 | 6 | |
| 5 | 2011 | 12 | |
| 6 | 2011 | 47 | |
| 7 | Pioglitazone for Diabetes Prevention in Impaired Glucose Tolerancebreakdown → | 2011 | 523 |
| 8 | 2010 | 18 | |
| 9 | 2010 | 1 | |
| 10 | 2010 | 30 | |
| 11 | 2010 | 23 | |
| 12 | 2010 | 45 | |
| 13 | 2009 | 16 | |
| 14 | 2009 | 30 | |
| 15 | 2007 | 28 | |
| 16 | 2005 | 48 | |
| 17 | 2005 | 349 | |
| 18 | 2002 | 9 | |
| 19 | 2001 | 74 | |
| 20 | 1988 | 4 |
About Ken Williams
Ken Williams is a scholar working on Endocrinology, Diabetes and Metabolism, Issues, ethics and legal aspects and Epidemiology, having authored 98 papers that have together received 12.3k indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (52 papers), Lipoproteins and Cardiovascular Health (25 papers), Liver Disease Diagnosis and Treatment (13 papers), Adipokines, Inflammation, and Metabolic Diseases (11 papers), Health Systems, Economic Evaluations, Quality of Life (10 papers), Diabetes Management and Research (9 papers), Obesity, Physical Activity, Diet (7 papers) and Metabolism, Diabetes, and Cancer (7 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (6.3k citations), Cardiology and Cardiovascular Medicine (2.3k citations) and Epidemiology (3.2k citations). Ken Williams has collaborated with scholars based in United States, Canada and Mexico. Frequent co-authors include Michael P. Stern, Steven M. Haffner, Kelly J. Hunt, Ralph B. D’Agostino, Carlos Lorenzo, Anthony J. Hanley, Allan D. Sniderman, Inmaculada del Rincón, Gregory L. Freeman and Agustín Escalante. Their work appears in journals such as Diabetes Care, Diabetes, Circulation, Journal of Vascular Surgery and Journal of clinical lipidology.
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.