Laura E. Mantella

750 total citations
30 papers, 415 citations indexed

About

Laura E. Mantella is a scholar working on Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Laura E. Mantella has authored 30 papers receiving a total of 415 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Cardiology and Cardiovascular Medicine, 16 papers in Pulmonary and Respiratory Medicine and 15 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Laura E. Mantella's work include Cardiovascular Health and Disease Prevention (15 papers), Cardiac Imaging and Diagnostics (13 papers) and Cerebrovascular and Carotid Artery Diseases (13 papers). Laura E. Mantella is often cited by papers focused on Cardiovascular Health and Disease Prevention (15 papers), Cardiac Imaging and Diagnostics (13 papers) and Cerebrovascular and Carotid Artery Diseases (13 papers). Laura E. Mantella collaborates with scholars based in Canada, Italy and India. Laura E. Mantella's co-authors include Amer M. Johri, Luca Saba, Ankush D. Jamthikar, Marie‐France Hétu, Joseph Abunassar, Kiera Liblik, John R. Laird, Deep Gupta, Jasjit S. Suri and Steven B. Feinstein and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Journal of the American College of Cardiology.

In The Last Decade

Laura E. Mantella

26 papers receiving 411 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Laura E. Mantella Canada	10	168	162	108	97	64	30	415
Mathias Kaspar Germany	12	135 0.8×	148 0.9×	69 0.6×	64 0.7×	120 1.9×	52	499
Marie Guerraty United States	10	84 0.5×	210 1.3×	54 0.5×	60 0.6×	60 0.9×	28	343
Anna Teresińska Poland	10	70 0.4×	235 1.5×	118 1.1×	115 1.2×	183 2.9×	32	431
Yen‐Min Huang Taiwan	9	54 0.3×	90 0.6×	74 0.7×	18 0.2×	57 0.9×	26	281
Jiehua Li China	11	131 0.8×	59 0.4×	63 0.6×	30 0.3×	99 1.5×	43	359
Beibei Jiang China	14	260 1.5×	69 0.4×	378 3.5×	23 0.2×	50 0.8×	33	582
Serena Dell’Aversana Italy	14	69 0.4×	171 1.1×	211 2.0×	47 0.5×	108 1.7×	28	400
Qiugen Hu China	11	136 0.8×	26 0.2×	188 1.7×	27 0.3×	63 1.0×	35	477
Lewis D. Hahn United States	11	180 1.1×	121 0.7×	86 0.8×	42 0.4×	52 0.8×	33	371
Gabriela Quiroga‐Garza United States	10	161 1.0×	40 0.2×	127 1.2×	38 0.4×	122 1.9×	31	424

Countries citing papers authored by Laura E. Mantella

Since Specialization

Citations

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

Fields of papers citing papers by Laura E. Mantella

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Laura E. Mantella. 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 Laura E. Mantella. The network helps show where Laura E. Mantella may publish in the future.

Co-authorship network of co-authors of Laura E. Mantella

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

All Works

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20 of 20 papers shown

Grubic, Nicholas, Matthew Fraser, Laura E. Mantella, et al.. (2025). ‘I wish I had been better prepared’: a mixed-methods study of psychological reactions, perceptions and opinions of cardiovascular preparticipation screening among young competitive athletes. British Journal of Sports Medicine. 59(11). 761–773.

Mantella, Laura E., Kiera Liblik, Marie‐France Hétu, et al.. (2025). Carotid Plaque Border Ulceration is Associated With Coronary Artery Disease and Future Cardiovascular Events. Canadian Journal of Cardiology.

Das, Suchismita, Gavino Faa, Manudeep Kalra, et al.. (2025). Preventive, personalized, and precision medicine and biomarkers for breast cancer diagnosis: Artificial intelligence framework. 7. 100045–100045.

Tiwari, Ekta, Mustafa Al-Maini, Rajesh Singh, et al.. (2025). Artificial intelligence-based multiclass diabetes risk stratification for big data embedded with explainability: From machine learning to attention models. Biomedical Signal Processing and Control. 106. 107672–107672. 1 indexed citations

Shrimankar, Deepti D., Mahesh Maindarkar, Mrinalini Bhagawati, et al.. (2025). Artificial intelligence-based cardiovascular/stroke risk stratification in women affected by autoimmune disorders: a narrative survey. Rheumatology International. 45(1). 14–14. 1 indexed citations

Saba, Luca, Mahesh Maindarkar, Amer M. Johri, et al.. (2024). UltraAIGenomics: Artificial Intelligence-Based Cardiovascular Disease Risk Assessment by Fusion of Ultrasound-Based Radiomics and Genomics Features for Preventive, Personalized and Precision Medicine: A Narrative Review. Reviews in Cardiovascular Medicine. 25(5). 184–184. 7 indexed citations

Bhagawati, Mrinalini, Sudip Paul, Laura E. Mantella, et al.. (2024). Cardiovascular Disease Risk Stratification Using Hybrid Deep Learning Paradigm: First of Its Kind on Canadian Trial Data. Diagnostics. 14(17). 1894–1894. 5 indexed citations

Hétu, Marie‐France, et al.. (2024). The association of carotid plaque burden and composition and the coronary artery calcium score in intermediate cardiovascular risk patients. The International Journal of Cardiovascular Imaging. 40(8). 1683–1692. 2 indexed citations

Saba, Luca, Mahesh Maindarkar, Narendra N. Khanna, et al.. (2023). A Pharmaceutical Paradigm for Cardiovascular Composite Risk Assessment Using Novel Radiogenomics Risk Predictors in Precision Explainable Artificial Intelligence Framework: Clinical Trial Tool. Frontiers in Bioscience-Landmark. 28(10). 248–248. 6 indexed citations

10.

Mantella, Laura E., et al.. (2023). A Novel Ultrasound-Based Carotid Plaque Vulnerability Score Is Associated With Long-Term Cardiovascular Outcomes. Journal of the American Society of Echocardiography. 36(11). 1217–1219.

11.

Johri, Amer M., Krishna V. Singh, Laura E. Mantella, et al.. (2022). Deep learning artificial intelligence framework for multiclass coronary artery disease prediction using combination of conventional risk factors, carotid ultrasound, and intraplaque neovascularization. Computers in Biology and Medicine. 150. 106018–106018. 27 indexed citations

12.

Mantella, Laura E., Kiera Liblik, & Amer M. Johri. (2021). Vascular imaging of atherosclerosis: Strengths and weaknesses. Atherosclerosis. 319. 42–50. 32 indexed citations

13.

Jamthikar, Ankush D., Deep Gupta, Laura E. Mantella, et al.. (2021). Ensemble Machine Learning and Its Validation for Prediction of Coronary Artery Disease and Acute Coronary Syndrome Using Focused Carotid Ultrasound. IEEE Transactions on Instrumentation and Measurement. 71. 1–10. 20 indexed citations

14.

Johri, Amer M., Laura E. Mantella, Ankush D. Jamthikar, et al.. (2021). Role of artificial intelligence in cardiovascular risk prediction and outcomes: comparison of machine-learning and conventional statistical approaches for the analysis of carotid ultrasound features and intra-plaque neovascularization. International journal of cardiac imaging. 37(11). 3145–3156. 20 indexed citations

15.

Mantella, Laura E., et al.. (2021). Femoral plaque burden by ultrasound is a better indicator of significant coronary artery disease over ankle brachial index. International journal of cardiac imaging. 37(10). 2965–2973. 7 indexed citations

16.

Mantella, Laura E., Winnie Chan, Gianluigi Bisleri, et al.. (2020). The use of ultrasound to assess aortic biomechanics: Implications for aneurysm and dissection. Echocardiography. 37(11). 1844–1850. 5 indexed citations

17.

Jamthikar, Ankush D., Deep Gupta, Amer M. Johri, et al.. (2020). Low-Cost Office-Based Cardiovascular Risk Stratification Using Machine Learning and Focused Carotid Ultrasound in an Asian-Indian Cohort. Journal of Medical Systems. 44(12). 208–208. 16 indexed citations

18.

Mantella, Laura E., et al.. (2019). Combined Femoral and Carotid Plaque Burden Identifies Obstructive Coronary Artery Disease in Women. Journal of the American Society of Echocardiography. 33(1). 90–100. 18 indexed citations

19.

Mantella, Laura E., et al.. (2018). Handheld versus conventional vascular ultrasound for assessing carotid artery plaque. International Journal of Cardiology. 278. 295–299. 8 indexed citations

20.

Singh, Krishna K., Fina Lovren, Yi Pan, et al.. (2014). The Essential Autophagy Gene ATG7 Modulates Organ Fibrosis via Regulation of Endothelial-to-Mesenchymal Transition. Journal of Biological Chemistry. 290(5). 2547–2559. 96 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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