Zeineb Bouzid

629 total citations · 1 hit paper
14 papers, 368 citations indexed

About

Zeineb Bouzid is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Cognitive Neuroscience. According to data from OpenAlex, Zeineb Bouzid has authored 14 papers receiving a total of 368 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cardiology and Cardiovascular Medicine, 3 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Cognitive Neuroscience. Recurrent topics in Zeineb Bouzid's work include ECG Monitoring and Analysis (8 papers), Acute Myocardial Infarction Research (6 papers) and Cardiac Imaging and Diagnostics (3 papers). Zeineb Bouzid is often cited by papers focused on ECG Monitoring and Analysis (8 papers), Acute Myocardial Infarction Research (6 papers) and Cardiac Imaging and Diagnostics (3 papers). Zeineb Bouzid collaborates with scholars based in United States, Canada and Jordan. Zeineb Bouzid's co-authors include Salah S. Al‐Zaiti, Ervin Sejdić, Clifton W. Callaway, Christian Martin‐Gill, Richard E. Gregg, Samir Saba, Ziad Faramand, Stephanie Frisch, Raymond Bond and Susan M. Sereika and has published in prestigious journals such as Circulation, Nature Medicine and Nature Communications.

In The Last Decade

Zeineb Bouzid

11 papers receiving 361 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.

Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction

2023 134 citations Salah S. Al‐Zaiti, Christian Martin‐Gill et al. Nature Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zeineb Bouzid United States	6	255	78	52	43	43	14	368
Ziad Faramand United States	10	307 1.2×	103 1.3×	54 1.0×	31 0.7×	42 1.0×	24	433
Michal Cohen‐Shelly United States	7	267 1.0×	76 1.0×	52 1.0×	23 0.5×	23 0.5×	14	354
Irena Andršová Czechia	11	213 0.8×	54 0.7×	40 0.8×	10 0.2×	27 0.6×	27	305
Arjan Sammani Netherlands	13	275 1.1×	24 0.3×	15 0.3×	9 0.2×	59 1.4×	20	386
Hisaki Makimoto Germany	18	1.1k 4.2×	56 0.7×	16 0.3×	19 0.4×	13 0.3×	73	1.2k
Manuel Marina‐Breysse Spain	7	168 0.7×	62 0.8×	25 0.5×	9 0.2×	8 0.2×	20	220
Jelle C L Himmelreich Netherlands	11	280 1.1×	39 0.5×	7 0.1×	16 0.4×	9 0.2×	29	332
Kristian Hellenkamp Germany	11	324 1.3×	86 1.1×	5 0.1×	10 0.2×	10 0.2×	24	469
Cheuk To Chung China	10	109 0.4×	21 0.3×	17 0.3×	14 0.3×	7 0.2×	24	240
J. Sajeev Australia	12	339 1.3×	35 0.4×	9 0.2×	31 0.7×	6 0.1×	33	442

Countries citing papers authored by Zeineb Bouzid

Since Specialization

Citations

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

Fields of papers citing papers by Zeineb Bouzid

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zeineb Bouzid

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

All Works

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14 of 14 papers shown

Bouzid, Zeineb, Ervin Sejdić, Christian Martin‐Gill, et al.. (2025). Electrocardiogram-based machine learning for risk stratification of patients with suspected acute coronary syndrome. European Heart Journal. 46(10). 943–954. 5 indexed citations

Akçakaya, Murat, Zeineb Bouzid, Tanmay Gokhale, et al.. (2025). ECG-SMART-NET: A Deep Learning Architecture for Precise ECG Diagnosis of Occlusion Myocardial Infarction. IEEE Transactions on Biomedical Engineering. 72(12). 3613–3620. 1 indexed citations

Yang, Yi, Zeineb Bouzid, R. A. Bull, et al.. (2025). Decoding depression: Event related potential dynamics and predictive neural signatures of depression severity. Journal of Affective Disorders. 391. 119893–119893.

Sharma, Deepak, Zeineb Bouzid, Neil Harris, et al.. (2025). Prescreening depression using wearable electrocardiogram and photoplethysmogram data from a psycholinguistic experiment. Physiological Measurement. 46(8). 85004–85004.

Al‐Zaiti, Salah S., Christian Martin‐Gill, Jessica K. Zègre‐Hemsey, et al.. (2023). Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction. Nature Medicine. 29(7). 1804–1813. 134 indexed citations breakdown →

Sereika, Susan M., Zeineb Bouzid, Gavin Hickey, et al.. (2023). Unsupervised machine learning identifies symptoms of indigestion as a predictor of acute decompensation and adverse cardiac events in patients with heart failure presenting to the emergency department. Heart & Lung. 61. 107–113. 4 indexed citations

Bouzid, Zeineb, Ziad Faramand, Salah S. Al‐Zaiti, & Ervin Sejdić. (2022). Abstract 15435: Evaluating Sex-Disparities in Machine Learning Decision Support Tools for Acute Coronary Syndrome Classification in the Emergency Department. Circulation. 146(Suppl_1).

Bouzid, Zeineb, Salah S. Al‐Zaiti, Raymond Bond, & Ervin Sejdić. (2022). Remote and wearable ECG devices with diagnostic abilities in adults: A state-of-the-science scoping review. Heart Rhythm. 19(7). 1192–1201. 42 indexed citations

Bouzid, Zeineb, Ziad Faramand, Christian Martin‐Gill, et al.. (2022). Incorporation of Serial 12-Lead Electrocardiogram With Machine Learning to Augment the Out-of-Hospital Diagnosis of Non-ST Elevation Acute Coronary Syndrome. Annals of Emergency Medicine. 81(1). 57–69. 13 indexed citations

10.

Gregg, Richard E., et al.. (2022). ECG detection of ACS by convolutional neural network utilizing transfer learning. Journal of Electrocardiology. 73. 18–19. 1 indexed citations

11.

Bouzid, Zeineb, Ziad Faramand, Richard E. Gregg, et al.. (2021). In Search of an Optimal Subset of ECG Features to Augment the Diagnosis of Acute Coronary Syndrome at the Emergency Department. Journal of the American Heart Association. 10(3). e017871–e017871. 32 indexed citations

12.

Faramand, Ziad, Mohammad Alrawashdeh, Stephanie Helman, et al.. (2021). Your neighborhood matters: A machine‐learning approach to the geospatial and social determinants of health in 9‐1‐1 activated chest pain. Research in Nursing & Health. 45(2). 230–239. 2 indexed citations

13.

Bouzid, Zeineb, Ziad Faramand, Richard E. Gregg, et al.. (2021). Novel ECG features and machine learning to optimize culprit lesion detection in patients with suspected acute coronary syndrome. Journal of Electrocardiology. 69. 31–37. 12 indexed citations

14.

Al‐Zaiti, Salah S., Zeineb Bouzid, Ziad Faramand, et al.. (2020). Machine learning-based prediction of acute coronary syndrome using only the pre-hospital 12-lead electrocardiogram. Nature Communications. 11(1). 3966–3966. 122 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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