Stephen Nolan

463 citations
18 papers · 270 · h-index 9

Impact in

Papers in

Stephen Nolan

18 papers receiving 264 citations

Peers

Stephen Nolan
Comparison fields: 5 of 74
  • Nephrology 137
  • Endocrinology, Diabetes and Metabolism 79
  • Health Informatics 3
  • Transplantation 6
  • Cardiology and Cardiovascular Medicine 49
Replace Salvatore Barone with:
Salvatore Barone United Kingdom
Sana Fathima India
Laura Solá Spain
Syed Saad Canada
Bilal Qarni Canada
Juan José García Sánchez United Kingdom
Jenny Wei United States
John Geen United Kingdom
Carolyn Bauer United States
Laurel Thorlacius Canada
Stephen Nolan relative to Salvatore Barone United Kingdom Salvatore Barone's profile →
Citations per field
00.5×4.5×
Salvatore Barone · 1×
Citations per year

Countries citing papers authored by Stephen Nolan

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Nolan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2020111
2 202122
3 202222
4 202220
5 202417
6 202314
7 202211
8 202210
9 20219
10 20228
11 20197
12 20245
13 20243
14 20233
15 20123
16 20133
17 20251
18 20211

About Stephen Nolan

Stephen Nolan is a scholar working on Nephrology, Endocrinology, Diabetes and Metabolism, Economics and Econometrics, Cardiology and Cardiovascular Medicine and Surgery, having authored 18 papers that have together received 270 indexed citations. Recurring topics across this work include Chronic Kidney Disease and Diabetes (13 papers), Dialysis and Renal Disease Management (8 papers), Diabetes Treatment and Management (7 papers), Renal Diseases and Glomerulopathies (3 papers), Health Systems, Economic Evaluations, Quality of Life (3 papers), Blood Pressure and Hypertension Studies (3 papers), Healthcare Policy and Management (2 papers) and Diabetes Management and Research (1 paper). The work is most often cited by research in Nephrology (137 citations), Endocrinology, Diabetes and Metabolism (79 citations), Health Informatics (3 citations), Transplantation (6 citations) and Cardiology and Cardiovascular Medicine (49 citations). Stephen Nolan has collaborated with scholars based in United Kingdom, United States and Sweden. Frequent co-authors include Juan José García Sánchez, Glen James, Roberto Pecoits‐Filho, Eric Wittbrodt, Elisabeth Sörstadius, Katherine R. Tuttle, Anna Bobrowska, David C. Wheeler, Carol A. Pollock and Matthew Arnold. Their work appears in journals such as Advances in Therapy, Kidney International Reports, Nephrology Dialysis Transplantation, Clinical Kidney Journal and Clinical 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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