William Siler

48 papers receiving 1.7k citations

Peers

William Siler
Comparison fields: 5 of 164
  • Cardiology and Cardiovascular Medicine 395
  • Artificial Intelligence 545
  • Statistics and Probability 127
  • Control and Systems Engineering 341
  • Aging 26
Replace Roland Fried with:
Roland Fried Germany
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Robin Genuer France
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M. J. Crowder United Kingdom
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William Siler relative to Roland Fried Germany Roland Fried's profile →
Citations per field
00.5×3.4×
Roland Fried · 1×
Citations per year

Countries citing papers authored by William Siler

Since Specialization
Citations

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

Fields of papers citing papers by William Siler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1990356
2 2004300
3 1979270
4 2004205
5 198679
6 198977
7 200563
8 198353
9 200150
10 199145
11 199033
12 200733
13 196931
14 196925
15 196622
16 197319
17 199918
18 198716
19 197416
20 196616

About William Siler

William Siler is a scholar working on Artificial Intelligence, Management Science and Operations Research, Biomedical Engineering, Surgery and Statistics and Probability, having authored 50 papers that have together received 1.9k indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (15 papers), Multi-Criteria Decision Making (8 papers), Fuzzy Systems and Optimization (5 papers), Cardiac Structural Anomalies and Repair (4 papers), Mechanical Circulatory Support Devices (4 papers), Cardiac Valve Diseases and Treatments (4 papers), Marine animal studies overview (3 papers) and Underwater Acoustics Research (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (395 citations), Artificial Intelligence (545 citations), Statistics and Probability (127 citations), Control and Systems Engineering (341 citations) and Aging (26 citations). William Siler has collaborated with scholars based in United States, Monaco and Japan. Frequent co-authors include James J. Buckley, Hao Ying, Philip E. Martin, Douglas M. Tucker, Gerald D. Buckberg, Marisa Di Donato, Constantine L. Athanasuleas, Alfred W.H. Stanley, Vincent Dor and Mehmet C. Öz. Their work appears in journals such as Fuzzy Sets and Systems, The Journal of the Acoustical Society of America, Annals of the New York Academy of Sciences, Medicine & Science in Sports & Exercise and The Journal of Clinical Endocrinology & Metabolism.

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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