Sam Friedman

2.1k citations
42 papers · 891 · 1 hit paper · h-index 16

Impact in

Papers in

Sam Friedman

41 papers receiving 874 citations

Sam Friedman's Hit Papers

ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation 2021 · 197 citations
1970+1+3Years since publication50100150

Peers

Sam Friedman
Comparison fields: 5 of 109
  • Health Informatics 26
  • Cardiology and Cardiovascular Medicine 326
  • Geology 42
  • Statistics, Probability and Uncertainty 42
  • Health Information Management 21
Replace Junyuan Shang with:
Junyuan Shang China
Shuo Zhou China
Brian E. Carlson United States
Thomas Lotz New Zealand
Julien Abinahed Qatar
Alfiia Galimzianova Slovenia
Samir S. Yadav India
Malik Sajjad Ahmed Nadeem Pakistan
Matthew Sinclair United Kingdom
Sam Friedman relative to Junyuan Shang China Junyuan Shang's profile →
Citations per field
00.5×10×20×30×42×
Junyuan Shang · 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 42 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 →
2021197
2 2020138
3 202161
4 202348
5 202344
6 202137
7 202232
8 201229
9 202328
10 202324
11 201924
12 201723
13 201218
14 201917
15 202317
16 202215
17 202414
18 202113
19 201113
20 202411

About Sam Friedman

Sam Friedman is a scholar working on Cardiology and Cardiovascular Medicine, Computational Theory and Mathematics, Statistics, Probability and Uncertainty, Environmental Engineering and Molecular Biology, having authored 42 papers that have together received 891 indexed citations. Recurring topics across this work include ECG Monitoring and Analysis (8 papers), Probabilistic and Robust Engineering Design (6 papers), Advanced Multi-Objective Optimization Algorithms (6 papers), Remote Sensing and LiDAR Applications (4 papers), Cardiovascular Function and Risk Factors (4 papers), Optimal Experimental Design Methods (3 papers), 3D Surveying and Cultural Heritage (3 papers) and Genetic Associations and Epidemiology (3 papers). The work is most often cited by research in Health Informatics (26 citations), Cardiology and Cardiovascular Medicine (326 citations), Geology (42 citations), Statistics, Probability and Uncertainty (42 citations) and Health Information Management (21 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, Puneet Batra, Shaan Khurshid, Ioannis Stamos, James P. Pirruccello, Douglas Allaire, Jennifer E. Ho and Paolo Di Achille. Their work appears in journals such as Circulation, npj Digital Medicine, Nature Communications, Journal of the American College of Cardiology and Bioinformatics.

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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