Christopher Reeder

671 total citations · 1 hit paper
20 papers, 274 citations indexed

About

Christopher Reeder is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Christopher Reeder has authored 20 papers receiving a total of 274 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cardiology and Cardiovascular Medicine, 4 papers in Molecular Biology and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Christopher Reeder's work include ECG Monitoring and Analysis (4 papers), Cardiovascular Function and Risk Factors (4 papers) and Cardiac Imaging and Diagnostics (3 papers). Christopher Reeder is often cited by papers focused on ECG Monitoring and Analysis (4 papers), Cardiovascular Function and Risk Factors (4 papers) and Cardiac Imaging and Diagnostics (3 papers). Christopher Reeder collaborates with scholars based in United States, Germany and Finland. Christopher Reeder's co-authors include Jennifer E. Ho, Steven A. Lubitz, Pulkit Singh, Shaan Khurshid, Puneet Batra, Paolo Di Achille, Patrick T. Ellinor, Anthony Philippakis, Sam Friedman and Mostafa A. Al‐Alusi and has published in prestigious journals such as Circulation, Nature Neuroscience and Journal of the American College of Cardiology.

In The Last Decade

Christopher Reeder

16 papers receiving 268 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation

2021 167 citations Shaan Khurshid, Sam Friedman et al. Circulation profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Christopher Reeder United States	7	187	44	23	23	22	20	274
Carolyn J. Park United States	6	257 1.4×	51 1.2×	11 0.5×	12 0.5×	30 1.4×	23	331
Rutger R van de Leur Netherlands	10	214 1.1×	28 0.6×	25 1.1×	42 1.8×	9 0.4×	24	269
Hidde Bleijendaal Netherlands	9	134 0.7×	20 0.5×	13 0.6×	33 1.4×	12 0.5×	12	191
Joshua Lampert United States	8	116 0.6×	33 0.8×	25 1.1×	28 1.2×	4 0.2×	32	196
Manuel Marina‐Breysse Spain	7	168 0.9×	62 1.4×	46 2.0×	8 0.3×	4 0.2×	20	220
Khaled Rjoob United Kingdom	7	58 0.3×	17 0.4×	13 0.6×	12 0.5×	7 0.3×	22	137
Wei-Yin Ko United States	4	168 0.9×	44 1.0×	42 1.8×	31 1.3×	2 0.1×	7	218
Joon-myoung Kwon South Korea	5	232 1.2×	42 1.0×	60 2.6×	42 1.8×	3 0.1×	6	296
Irene E. Hof Netherlands	9	429 2.3×	91 2.1×	13 0.6×	7 0.3×	20 0.9×	12	474
Graham Cole United Kingdom	5	76 0.4×	44 1.0×	8 0.3×	15 0.7×	10 0.5×	12	199

Countries citing papers authored by Christopher Reeder

Since Specialization

Citations

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

Fields of papers citing papers by Christopher Reeder

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christopher Reeder

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher Reeder. A scholar is included among the top collaborators of Christopher Reeder 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 Christopher Reeder. Christopher Reeder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Friedman, Sam, Shaan Khurshid, Xin Wang, et al.. (2025). Unsupervised deep learning of electrocardiograms enables scalable human disease profiling. npj Digital Medicine. 8(1). 23–23. 4 indexed citations

Al‐Alusi, Mostafa A., Emily S. Lau, Christopher Reeder, et al.. (2025). A Deep Learning Model to Identify Mitral Valve Prolapse From the Echocardiogram. JACC. Cardiovascular imaging. 19(1). 18–29.

Lau, Emily S., V. D’Souza, Yunong Zhao, et al.. (2025). Contemporary Burden of Cardiovascular Disease in Pregnancy: Insights From a Real-World Pregnancy Electronic Health Record Cohort. Circulation. 152(15). 1044–1055.

Kany, Shinwan, Sam Friedman, Mostafa A. Al‐Alusi, et al.. (2025). Electrocardiogram-Based Artificial Intelligence to Identify Coronary Artery Disease. JACC Advances. 4(9). 102041–102041. 1 indexed citations

Al‐Alusi, Mostafa A., Sam Friedman, Joel Rämö, et al.. (2025). A deep learning digital biomarker to detect hypertension and stratify cardiovascular risk from the electrocardiogram. npj Digital Medicine. 8(1). 120–120. 3 indexed citations

Haimovich, Julian S., Paolo Di Achille, Victor Nauffal, et al.. (2024). Frequency of Electrocardiogram-Defined Cardiac Conduction Disorders in a Multi-Institutional Primary Care Cohort. JACC Advances. 3(7). 101004–101004. 4 indexed citations

Reeder, Christopher, Brian Claggett, Pulkit Singh, et al.. (2024). Natural Language Processing to Adjudicate Heart Failure Hospitalizations in Global Clinical Trials. Circulation Heart Failure. 18(1). e012514–e012514. 1 indexed citations

Lau, Emily S., Paolo Di Achille, Pulkit Singh, et al.. (2023). Deep Learning–Enabled Assessment of Left Heart Structure and Function Predicts Cardiovascular Outcomes. Journal of the American College of Cardiology. 82(20). 1936–1948. 27 indexed citations

Wang, Xin, Shaan Khurshid, Seung Hoan Choi, et al.. (2023). Genetic Susceptibility to Atrial Fibrillation Identified via Deep Learning of 12-Lead Electrocardiograms. Circulation Genomic and Precision Medicine. 16(4). 340–349. 7 indexed citations

10.

Khurshid, Shaan, Timothy W. Churchill, Nathaniel Diamant, et al.. (2023). Deep learned representations of the resting 12-lead electrocardiogram to predict at peak exercise. European Journal of Preventive Cardiology. 31(2). 252–262. 6 indexed citations

11.

Haimovich, Julian S., Shaan Khurshid, Paolo Di Achille, et al.. (2023). Artificial intelligence–enabled classification of hypertrophic heart diseases using electrocardiograms. PubMed. 4(2). 48–59. 23 indexed citations

12.

Singh, Pulkit, Julian S. Haimovich, Christopher Reeder, et al.. (2022). One Clinician Is All You Need–Cardiac Magnetic Resonance Imaging Measurement Extraction: Deep Learning Algorithm Development. JMIR Medical Informatics. 10(9). e38178–e38178. 9 indexed citations

13.

Harrington, Lia X., Shaan Khurshid, Mostafa A. Al‐Alusi, et al.. (2022). A Machine Learning Approach to Automate Ischemic Stroke Subtyping (N2.001). Neurology. 98(18_supplement). 1 indexed citations

14.

Haimovich, Julian S., Shaan Khurshid, Paolo Di Achille, et al.. (2021). Abstract 10587: Frequency and Outcomes of Bradyarrhythmias in the Community. Circulation. 144(Suppl_1).

15.

Khurshid, Shaan, Sam Friedman, Christopher Reeder, et al.. (2021). Abstract 12922: Electrocardiogram-Based Deep Learning and Clinical Risk Factors to Predict Incident Atrial Fibrillation. Circulation. 144(Suppl_1). 2 indexed citations

16.

Khurshid, Shaan, Sam Friedman, Christopher Reeder, et al.. (2021). ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation. Circulation. 145(2). 122–133. 167 indexed citations breakdown →

17.

Dryden, Michael W., et al.. (2016). Comparison of parasitic mite retrieval methods in a population of community cats. Journal of Feline Medicine and Surgery. 19(6). 657–664. 9 indexed citations

18.

Reeder, Christopher, Michael Closser, Huay Mei Poh, et al.. (2015). High Resolution Mapping of Enhancer-Promoter Interactions. PLoS ONE. 10(5). e0122420–e0122420. 6 indexed citations

19.

Mazzoni, Esteban O., Shaun Mahony, Mirza Peljto, et al.. (2013). Saltatory remodeling of Hox chromatin in response to rostrocaudal patterning signals. Nature Neuroscience. 16(9). 1191–1198. 4 indexed citations

20.

Lévy, Dan, Christopher Reeder, Bradford D. Loucas, et al.. (2007). Interpreting Chromosome Aberration Spectra. Journal of Computational Biology. 14(2). 144–155.

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.

Explore authors with similar magnitude of impact