John M. Pfeifer

714 total citations
6 papers, 65 citations indexed

About

John M. Pfeifer is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Health Information Management. According to data from OpenAlex, John M. Pfeifer has authored 6 papers receiving a total of 65 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cardiology and Cardiovascular Medicine, 2 papers in Radiology, Nuclear Medicine and Imaging and 1 paper in Health Information Management. Recurrent topics in John M. Pfeifer's work include ECG Monitoring and Analysis (2 papers), Atrial Fibrillation Management and Outcomes (2 papers) and Sex and Gender in Healthcare (1 paper). John M. Pfeifer is often cited by papers focused on ECG Monitoring and Analysis (2 papers), Atrial Fibrillation Management and Outcomes (2 papers) and Sex and Gender in Healthcare (1 paper). John M. Pfeifer collaborates with scholars based in United States. John M. Pfeifer's co-authors include Brandon K. Fornwalt, Christopher M. Haggerty, Sushravya Raghunath, David P. vanMaanen, H. Lester Kirchner, Alvaro Ulloa, Jonathan D Suever, Joseph B. Leader, Linyuan Jing and Dustin N. Hartzel and has published in prestigious journals such as Circulation, Nature Biomedical Engineering and Heart Rhythm.

In The Last Decade

John M. Pfeifer

4 papers receiving 64 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
John M. Pfeifer United States	4	37	35	9	9	8	6	65
Hirotaka Ieki Japan	3	19 0.5×	22 0.6×	9 1.0×	12 1.3×	4 0.5×	6	44
Yaacoub Chahine United States	6	70 1.9×	19 0.5×	8 0.9×	5 0.6×	7 0.9×	19	94
Amro Alsaid United States	5	96 2.6×	31 0.9×	10 1.1×	9 1.0×	6 0.8×	21	140
Yunxin Zhong China	3	11 0.3×	39 1.1×	13 1.4×	16 1.8×	8 1.0×	3	49
Ahmed Harouni United States	5	22 0.6×	26 0.7×	5 0.6×	17 1.9×	19 2.4×	6	73
Zhubo Jiang Singapore	4	47 1.3×	41 1.2×	9 1.0×	2 0.2×	3 0.4×	5	65
Michael Bereket United States	2	8 0.2×	24 0.7×	7 0.8×	22 2.4×	5 0.6×	3	87
Wenbin Wei China	5	15 0.4×	39 1.1×	5 0.6×	2 0.2×	7 0.9×	10	70
Jie Shi China	5	19 0.5×	35 1.0×	29 3.2×	16 1.8×	9 1.1×	10	64
Crystal Chun Yuen Chong Singapore	6	10 0.3×	132 3.8×	5 0.6×	8 0.9×	8 1.0×	16	191

Countries citing papers authored by John M. Pfeifer

Since Specialization

Citations

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

Fields of papers citing papers by John M. Pfeifer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John M. Pfeifer. 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 John M. Pfeifer. The network helps show where John M. Pfeifer may publish in the future.

Co-authorship network of co-authors of John M. Pfeifer

This figure shows the co-authorship network connecting the top 25 collaborators of John M. Pfeifer. A scholar is included among the top collaborators of John M. Pfeifer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John M. Pfeifer. John M. Pfeifer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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6 of 6 papers shown

1.

Jing, Linyuan, Thomas Morland, Sushravya Raghunath, et al.. (2025). Machine learning–enabled assessment of risk of drug-induced QT prolongation at the time of prescribing. Heart Rhythm.

2.

Ulloa, Alvaro, Sushravya Raghunath, David P. vanMaanen, et al.. (2022). Abstract 11000: Deep Learning Prediction of New-Onset Atrial Fibrillation Using Echocardiography Videos. Circulation. 146(Suppl_1).

3.

Raghunath, Sushravya, John M. Pfeifer, Chris R. Kelsey, et al.. (2022). An ECG-based machine learning model for predicting new-onset atrial fibrillation is superior to age and clinical features in identifying patients at high stroke risk. Journal of Electrocardiology. 76. 61–65. 6 indexed citations

4.

Ulloa, Alvaro, Linyuan Jing, Christopher W. Good, et al.. (2021). Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality. Nature Biomedical Engineering. 5(6). 546–554. 45 indexed citations

5.

Stough, Joshua V., Sushravya Raghunath, Xiaoyan Zhang, et al.. (2020). Left ventricular and atrial segmentation of 2D echocardiography with convolutional neural networks. 9–9. 10 indexed citations

6.

Ladapo, Joseph A., et al.. (2018). Quantifying Sex Differences in Cardiovascular Care Among Patients Evaluated for Suspected Ischemic Heart Disease. Journal of Women s Health. 28(5). 698–704. 4 indexed citations

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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