Steve Riley

4.3k citations
40 papers · 1.2k indexed · h-index 15

Steve Riley

38 papers receiving 1.1k citations

Peers

Steve Riley
Comparison fields: 5 of 103
  • Cardiology and Cardiovascular Medicine 373
  • Nephrology 111
  • Statistics and Probability 84
  • Molecular Biology 626
  • Genetics 92
Replace Jörg Täubel with:
Jörg Täubel United Kingdom
Bo Jin China
Ann M. Moyer United States
Bhawna Singh India
Françoise Imbert‐Bismut France
MO Karlsson Sweden
Bin Zhao China
Julia M. Barbarino United States
Tisha Joy Canada
Michael T. Eadon United States
Steve Riley relative to Jörg Täubel United Kingdom Jörg Täubel's profile →
Citations per field
00.5×2.9×
Jörg Täubel · 1×
Citations per year

Countries citing papers authored by Steve Riley

Since Specialization
Citations

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

Fields of papers citing papers by Steve Riley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 202312
3 20222
4 202110
5 202131
6 2020124
7 20206
8 20191
9 20192
10 2017170
11
Modeling the Neuropsychiatric Inventory (NPI) - Strengths and Weaknesses of a Multidimensional Item Response Theory Approach
20151
12 201418
13 201448
14 201320
15 201381
16 20121
17 201010
18 200912
19
Protect Your Windows Network: From Perimeter to Data (Microsoft Technology)
20052
20 200317

About Steve Riley

Steve Riley is a scholar working on Family Practice, Medical Laboratory Technology and Statistics and Probability, having authored 40 papers that have together received 1.2k indexed citations. Recurring topics across this work include Cardiac electrophysiology and arrhythmias (11 papers), Amyloidosis: Diagnosis, Treatment, Outcomes (9 papers), Computational Drug Discovery Methods (5 papers), Eosinophilic Disorders and Syndromes (5 papers), Statistical Methods in Clinical Trials (5 papers), Peptidase Inhibition and Analysis (4 papers), Receptor Mechanisms and Signaling (4 papers) and Coagulation, Bradykinin, Polyphosphates, and Angioedema (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (373 citations), Nephrology (111 citations) and Statistics and Probability (84 citations). Steve Riley has collaborated with scholars based in United States, United Kingdom and Sweden. Frequent co-authors include Christine Garnett, Georg Ferber, Giampaolo Merlini, Daniel P. Judge, Marla B. Sultan, Philip T. Sager, Nenad Sarapa, James J. Keirns, Charles Benson and Börje Darpö. Their work appears in journals such as The Journal of Clinical Pharmacology, Journal of Pharmacokinetics and Pharmacodynamics, CPT Pharmacometrics & Systems Pharmacology, British Journal of Clinical Pharmacology and Journal of Renal Care.

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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