Scott Kaplin

16 papers receiving 580 citations

Scott Kaplin's Hit Papers

Machine learning prediction in cardiovascular diseases: a meta-analysis 2020 · 310 citations
3100+2+4Years since publication100200300

Peers

Scott Kaplin
Comparison fields: 5 of 117
  • Health Informatics 57
  • Health Information Management 146
  • Medical Laboratory Technology 13
  • Cardiology and Cardiovascular Medicine 127
  • Aging 8
Replace Fatma Hilal Yağın with:
Fatma Hilal Yağın Türkiye
Feixiong Cheng United States
HongJu Zhang United States
Konstantia Zarkogianni Greece
Simon Lebech Cichosz Denmark
Md. Jahanur Rahman Bangladesh
Yikuan Li United Kingdom
Joseph El Youssef United States
Gurpreet Singh India
Ljiljana Trtica Majnarić Croatia
Scott Kaplin relative to Fatma Hilal Yağın Türkiye Fatma Hilal Yağın's profile →
Citations per field
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Fatma Hilal Yağın · 1×
Citations per year

Countries citing papers authored by Scott Kaplin

Since Specialization
Citations

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

Fields of papers citing papers by Scott Kaplin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1
Machine learning prediction in cardiovascular diseases: a meta-analysis
Hit paper breakdown →
2020310
2 202278
3 202148
4 202238
5 202133
6 202228
7 202320
8 201912
9 202111
10 202110
11 20217
12 20216
13 20234
14 20193
15 20193
16 20211
17 20170
18 20210

About Scott Kaplin

Scott Kaplin is a scholar working on Cardiology and Cardiovascular Medicine, Surgery, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Physiology, having authored 18 papers that have together received 612 indexed citations. Recurring topics across this work include Coronary Interventions and Diagnostics (2 papers), Spaceflight effects on biology (2 papers), Acute Myocardial Infarction Research (2 papers), Advanced Radiotherapy Techniques (1 paper), Fatty Acid Research and Health (1 paper), Radiation Therapy and Dosimetry (1 paper), Renal and Vascular Pathologies (1 paper) and Management of metastatic bone disease (1 paper). The work is most often cited by research in Health Informatics (57 citations), Health Information Management (146 citations), Medical Laboratory Technology (13 citations), Cardiology and Cardiovascular Medicine (127 citations) and Aging (8 citations). Scott Kaplin has collaborated with scholars based in United States, Belarus and Switzerland. Frequent co-authors include Chayakrit Krittanawong, Zhen Wang, Hafeez Ul Hassan Virk, W.H. Wilson Tang, Bharat Narasimhan, Kipp W. Johnson, Jonathan L. Halperin, Usman Baber, Rachel Pinotti and Takeshi Kitai. Their work appears in journals such as The American Journal of Medicine, The American Journal of Cardiology, Progress in Cardiovascular Diseases, European Heart Journal and Journal of the American College of 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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