Sam Friedman

2.0k citations
41 papers · 783 · 1 hit paper · h-index 15

Impact in

Papers in

Sam Friedman

40 papers receiving 766 citations

Sam Friedman's Hit Papers

ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation 2021 · 167 citations
1670+1+3Years since publication50100150

Peers

Sam Friedman
Comparison fields: 5 of 110
  • Health Informatics 27
  • Cardiology and Cardiovascular Medicine 373
  • Geology 39
  • Statistics, Probability and Uncertainty 38
  • Health Information Management 20
Replace Laura Azzimonti with:
Laura Azzimonti Switzerland
Olof Enqvist Sweden
Vanathi Gopalakrishnan United States
Rémi Dubois France
Brian E. Carlson United States
Michalis Zervakis Greece
Huazhen Wang China
Nina Zhou United States
Shilei Sun China
Sam Friedman relative to Laura Azzimonti Switzerland Laura Azzimonti's profile →
Citations per field
00.5×10×12.9×
Laura Azzimonti · 1×
Citations per year

Countries citing papers authored by Sam Friedman

Since Specialization
Citations

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

Fields of papers citing papers by Sam Friedman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1
ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation
Hit paper breakdown →
2021167
2 2020129
3 202155
4 202339
5 202135
6 202232
7 202330
8 201229
9 201924
10 202323
11 202323
12 201723
13 201216
14 201916
15 202215
16 202314
17 202112
18 201111
19 202410
20 20229

About Sam Friedman

Sam Friedman is a scholar working on Cardiology and Cardiovascular Medicine, Computational Theory and Mathematics, Molecular Biology, Genetics and Statistics, Probability and Uncertainty, having authored 41 papers that have together received 783 indexed citations. Recurring topics across this work include ECG Monitoring and Analysis (8 papers), Cardiovascular Function and Risk Factors (8 papers), Probabilistic and Robust Engineering Design (6 papers), Advanced Multi-Objective Optimization Algorithms (6 papers), Genetic Associations and Epidemiology (5 papers), Cardiac Imaging and Diagnostics (4 papers), Remote Sensing and LiDAR Applications (4 papers) and Atrial Fibrillation Management and Outcomes (4 papers). The work is most often cited by research in Health Informatics (27 citations), Cardiology and Cardiovascular Medicine (373 citations), Geology (39 citations), Statistics, Probability and Uncertainty (38 citations) and Health Information Management (20 citations). Sam Friedman has collaborated with scholars based in United States, Germany and Finland. Frequent co-authors include Anthony Philippakis, Patrick T. Ellinor, Steven A. Lubitz, Ioannis Stamos, Puneet Batra, Shaan Khurshid, Douglas Allaire, James P. Pirruccello, Jennifer E. Ho and Paolo Di Achille. Their work appears in journals such as Nature Communications, Circulation, npj Digital Medicine, Journal of the American College of Cardiology and Cell Genomics.

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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