Daniel S. Kushner

623 citations
24 papers · 463 indexed · h-index 11

Impact in

Papers in

Daniel S. Kushner

22 papers receiving 357 citations

Peers

Daniel S. Kushner
Comparison fields: 5 of 85
  • Nephrology 143
  • Cardiology and Cardiovascular Medicine 79
  • Pulmonary and Respiratory Medicine 107
  • Genetics 80
  • Endocrinology, Diabetes and Metabolism 41
Replace William B. Lorentz with:
William B. Lorentz United States
Joke van der Linden Netherlands
Anne Babler Germany
Steven D. Tennenberg United States
Harley C. Carlson United States
Thomas Savage United States
Teemu Honkanen Finland
Ivan Graber France
G A K Missen United Kingdom
Jan Carstens Denmark
Daniel S. Kushner relative to William B. Lorentz United States William B. Lorentz's profile →
Citations per field
00.5×3.0×
William B. Lorentz · 1×
Citations per year

Countries citing papers authored by Daniel S. Kushner

Since Specialization
Citations

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

Fields of papers citing papers by Daniel S. Kushner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel S. Kushner. 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 Daniel S. Kushner. The network helps show where Daniel S. Kushner may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20232
2 20231
3 20232
4 20230
5 20223
6 20221
7 19647
8 196120
9 196140
10 196138
11 196021
12 19604
13 196039
14 1958144
15
Effect of chlorpromazine upon experimental hepatic injury.
195710
16 19562
17 195610
18
Studies of serum mucoprotein (seromucoid). I. A turbidimetric method.
195632
19 19558
20 19554

About Daniel S. Kushner

Daniel S. Kushner is a scholar working on Nephrology, Endocrinology, Diabetes and Metabolism, Safety, Risk, Reliability and Quality, Rheumatology and Genetics, having authored 24 papers that have together received 463 indexed citations. Recurring topics across this work include Optimal Power Flow Distribution (3 papers), Cardiac electrophysiology and arrhythmias (3 papers), Smart Grid Energy Management (2 papers), Power System Reliability and Maintenance (2 papers), Parathyroid Disorders and Treatments (2 papers), Renal Diseases and Glomerulopathies (2 papers), Neurological and metabolic disorders (2 papers) and Microgrid Control and Optimization (2 papers). The work is most often cited by research in Nephrology (143 citations), Cardiology and Cardiovascular Medicine (79 citations), Pulmonary and Respiratory Medicine (107 citations), Genetics (80 citations) and Endocrinology, Diabetes and Metabolism (41 citations). Daniel S. Kushner has collaborated with scholars based in United States and China. Frequent co-authors include Alvin Dubin, David Bronsky, I. Snapper, Sheldon S. Waldstein, S. Howard Armstrong, A. S. Markowitz, Hans Pópper, J. de la Huerga, Paul B. Szanto and Ignacio Arribas. Their work appears in journals such as The American Journal of Medicine, The American Journal of Cardiology, Medicine, American Journal of Clinical Nutrition and Journal of Investigative Dermatology.

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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