Conner Galloway

502 citations
9 papers · 321 · 1 hit paper · h-index 5

Impact in

Papers in

Conner Galloway

7 papers receiving 316 citations

Conner Galloway's Hit Papers

Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram 2019 · 209 citations
2090+2+4Years since publication50100150200

Peers

Conner Galloway
Comparison fields: 5 of 52
  • Health Informatics 41
  • Cardiology and Cardiovascular Medicine 245
  • Health Information Management 26
  • Pulmonary and Respiratory Medicine 67
  • Cognitive Neuroscience 33
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Conner Galloway relative to Alexander Valys United States Alexander Valys's profile →
Citations per field
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Citations per year

Countries citing papers authored by Conner Galloway

Since Specialization
Citations

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

Fields of papers citing papers by Conner Galloway

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1
Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram
Hit paper breakdown →
2019209
2 202174
3 201814
4 202112
5 20196
6 20193
7 20243
8 20190
9 20230

About Conner Galloway

Conner Galloway is a scholar working on Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine, General Health Professions, Atomic and Molecular Physics, and Optics and Radiation, having authored 9 papers that have together received 321 indexed citations. Recurring topics across this work include ECG Monitoring and Analysis (4 papers), Cardiac electrophysiology and arrhythmias (3 papers), Potassium and Related Disorders (2 papers), Nuclear reactor physics and engineering (1 paper), Laser Design and Applications (1 paper), Mobile Health and mHealth Applications (1 paper), Cardiac Arrhythmias and Treatments (1 paper) and Heart Failure Treatment and Management (1 paper). The work is most often cited by research in Health Informatics (41 citations), Cardiology and Cardiovascular Medicine (245 citations), Health Information Management (26 citations), Pulmonary and Respiratory Medicine (67 citations) and Cognitive Neuroscience (33 citations). Conner Galloway has collaborated with scholars based in United States, New Zealand and Spain. Frequent co-authors include Paul A. Friedman, Zachi I. Attia, D.J. Albert, Michael J. Ackerman, Jacqueline Baras Shreibati, Peter A. Noseworthy, Rickey E. Carter, Alexander Valys, John Dillon and Samuel J. Asirvatham. Their work appears in journals such as Journal of the American College of Cardiology, JAMA Cardiology, Fusion Engineering and Design, Circulation and PLoS ONE.

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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