Pulkit Singh

614 total citations · 1 hit paper
13 papers, 252 citations indexed

About

Pulkit Singh is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Statistics, Probability and Uncertainty. According to data from OpenAlex, Pulkit Singh has authored 13 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cardiology and Cardiovascular Medicine, 2 papers in Molecular Biology and 2 papers in Statistics, Probability and Uncertainty. Recurrent topics in Pulkit Singh's work include ECG Monitoring and Analysis (3 papers), Meta-analysis and systematic reviews (2 papers) and Atrial Fibrillation Management and Outcomes (2 papers). Pulkit Singh is often cited by papers focused on ECG Monitoring and Analysis (3 papers), Meta-analysis and systematic reviews (2 papers) and Atrial Fibrillation Management and Outcomes (2 papers). Pulkit Singh collaborates with scholars based in United States, Germany and Switzerland. Pulkit Singh's co-authors include Jennifer E. Ho, Shaan Khurshid, Puneet Batra, Christopher Reeder, Steven A. Lubitz, Paolo Di Achille, Patrick T. Ellinor, Sam Friedman, Anthony Philippakis and Mostafa A. Al‐Alusi and has published in prestigious journals such as Circulation, Journal of the American College of Cardiology and Circulation Heart Failure.

In The Last Decade

Pulkit Singh

12 papers receiving 246 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
Pulkit Singh United States	6	184	44	23	21	20	13	252
Rutger R van de Leur Netherlands	10	214 1.2×	28 0.6×	42 1.8×	25 1.2×	42 2.1×	24	269
Irena Andršová Czechia	11	213 1.2×	54 1.2×	27 1.2×	32 1.5×	10 0.5×	27	305
Matthew M. Kalscheur United States	7	234 1.3×	24 0.5×	25 1.1×	19 0.9×	18 0.9×	16	319
Chih‐Min Liu Taiwan	11	280 1.5×	37 0.8×	10 0.4×	23 1.1×	22 1.1×	60	333
Joshua Lampert United States	8	116 0.6×	33 0.8×	28 1.2×	25 1.2×	21 1.1×	32	196
Michal Cohen‐Shelly United States	7	267 1.5×	76 1.7×	23 1.0×	50 2.4×	23 1.1×	14	354
Conner Galloway United States	5	245 1.3×	35 0.8×	39 1.7×	67 3.2×	33 1.6×	9	321
Martina Šišáková Czechia	11	267 1.5×	46 1.0×	27 1.2×	19 0.9×	16 0.8×	31	364
Wei-Yin Ko United States	4	168 0.9×	44 1.0×	31 1.3×	42 2.0×	32 1.6×	7	218
Manuel Marina‐Breysse Spain	7	168 0.9×	62 1.4×	8 0.3×	46 2.2×	9 0.5×	20	220

Countries citing papers authored by Pulkit Singh

Since Specialization

Citations

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

Fields of papers citing papers by Pulkit Singh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pulkit Singh

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

All Works

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13 of 13 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., 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

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

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

Kartoun, Uri, Akl C. Fahed, Shinwan Kany, et al.. (2023). Exploring the link between Gilbert’s syndrome and atherosclerotic cardiovascular disease: insights from a subpopulation-based analysis of over one million individuals. European Heart Journal Open. 3(3). oead059–oead059. 2 indexed citations

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

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

10.

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).

11.

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

12.

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 →

13.

Singh, Pulkit, et al.. (2020). End-to-end Deep Prototype and Exemplar Models for Predicting Human Behavior. eScholarship (California Digital Library). 1 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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