Mjaye Mazwi

1.3k total citations
51 papers, 724 citations indexed

About

Mjaye Mazwi is a scholar working on Surgery, Cardiology and Cardiovascular Medicine and Biomedical Engineering. According to data from OpenAlex, Mjaye Mazwi has authored 51 papers receiving a total of 724 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Surgery, 20 papers in Cardiology and Cardiovascular Medicine and 17 papers in Biomedical Engineering. Recurrent topics in Mjaye Mazwi's work include Congenital Heart Disease Studies (12 papers), Mechanical Circulatory Support Devices (11 papers) and Artificial Intelligence in Healthcare and Education (9 papers). Mjaye Mazwi is often cited by papers focused on Congenital Heart Disease Studies (12 papers), Mechanical Circulatory Support Devices (11 papers) and Artificial Intelligence in Healthcare and Education (9 papers). Mjaye Mazwi collaborates with scholars based in Canada, United States and Israel. Mjaye Mazwi's co-authors include Shalmali Joshi, Melissa D. McCradden, James A. Anderson, Danny Eytan, Lisa J. Martin, Meredith E. Tabangin, D. Woodrow Benson, Linda Cripe, Robert B. Hinton and Sebastian D. Goodfellow and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American College of Cardiology and PEDIATRICS.

In The Last Decade

Mjaye Mazwi

45 papers receiving 706 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mjaye Mazwi Canada 14 234 184 143 136 121 51 724
Kristin Corey United States 9 133 0.6× 76 0.4× 97 0.7× 149 1.1× 49 0.4× 20 516
Elizabeth A. Stephenson Canada 23 397 1.7× 848 4.6× 77 0.5× 244 1.8× 97 0.8× 75 1.4k
Mandy Rickard Canada 18 138 0.6× 48 0.3× 130 0.9× 238 1.8× 220 1.8× 119 1.0k
Jason M. Davies United States 13 121 0.5× 61 0.3× 39 0.3× 144 1.1× 58 0.5× 26 647
Neal Yuan United States 18 123 0.5× 696 3.8× 206 1.4× 122 0.9× 133 1.1× 36 1.4k
Vincent Nguyen United States 15 112 0.5× 50 0.3× 132 0.9× 245 1.8× 140 1.2× 76 841
Anirudh Sridharan United States 7 155 0.7× 61 0.3× 137 1.0× 73 0.5× 17 0.1× 8 677
Agam Bansal United States 19 241 1.0× 420 2.3× 32 0.2× 256 1.9× 88 0.7× 84 1.1k
Andre Kumar United States 13 225 1.0× 41 0.2× 85 0.6× 56 0.4× 103 0.9× 31 619
Joshua G. Kovoor Australia 13 73 0.3× 126 0.7× 45 0.3× 181 1.3× 67 0.6× 128 634

Countries citing papers authored by Mjaye Mazwi

Since Specialization
Citations

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

Fields of papers citing papers by Mjaye Mazwi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mjaye Mazwi

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

All Works

20 of 20 papers shown
1.
Mazwi, Mjaye, et al.. (2025). Noise is an underrecognized problem in medical decision making and is known by other names: a scoping review. BMC Medical Informatics and Decision Making. 25(1). 86–86. 1 indexed citations
2.
Mazwi, Mjaye, et al.. (2024). Artificial intelligence in medicine and the pursuit of environmentally responsible science. The Lancet Digital Health. 6(7). e438–e440. 4 indexed citations
3.
Goodwin, Andrew, William G Dixon, Mjaye Mazwi, et al.. (2023). The truth Hertz—synchronization of electroencephalogram signals with physiological waveforms recorded in an intensive care unit. Physiological Measurement. 44(8). 85002–85002. 1 indexed citations
4.
5.
Mazwi, Mjaye, et al.. (2023). AnnoDash, a clinical terminology annotation dashboard. JAMIA Open. 6(3). ooad046–ooad046. 2 indexed citations
6.
Joshi, Shalmali, et al.. (2023). Making machine learning matter to clinicians: model actionability in medical decision-making. npj Digital Medicine. 6(1). 7–7. 30 indexed citations
7.
Mazwi, Mjaye, et al.. (2023). iCVS—Inferring Cardio-Vascular hidden States from physiological signals available at the bedside. PLoS Computational Biology. 19(9). e1010835–e1010835.
8.
Jeewa, Aamir, Mjaye Mazwi, Emilie Jean‐St‐Michel, et al.. (2023). Canada’s First Successful Paediatric Total Artificial Heart Implant. SHILAP Revista de lepidopterología. 2(6). 494–497. 1 indexed citations
9.
Harish, Vinyas, et al.. (2022). Ignorance Isn't Bliss: We Must Close the Machine Learning Knowledge Gap in Pediatric Critical Care. Frontiers in Pediatrics. 10. 864755–864755. 3 indexed citations
10.
Jain, Amish, Regan E. Giesinger, Shyamala Dakshinamurti, et al.. (2022). Care of the critically ill neonate with hypoxemic respiratory failure and acute pulmonary hypertension: framework for practice based on consensus opinion of neonatal hemodynamics working group. Journal of Perinatology. 42(1). 3–13. 18 indexed citations
11.
Jegatheeswaran, Anusha, Sebastian D. Goodfellow, William G Dixon, et al.. (2022). Heart rate variability is markedly abnormal following surgical repair of atrial and ventricular septal defects in pediatric patients. SHILAP Revista de lepidopterología. 7. 100333–100333. 1 indexed citations
12.
McCradden, Melissa D., Shalmali Joshi, Mjaye Mazwi, & James A. Anderson. (2020). Ethical limitations of algorithmic fairness solutions in health care machine learning. The Lancet Digital Health. 2(5). e221–e223. 137 indexed citations
13.
Goodwin, Andrew, Danny Eytan, Mjaye Mazwi, et al.. (2020). A practical approach to storage and retrieval of high-frequency physiological signals. Physiological Measurement. 41(3). 35008–35008. 16 indexed citations
14.
Eckhauser, Aaron, Maria I. Van Rompay, Chitra Ravishankar, et al.. (2019). Variation in care for children undergoing the Fontan operation for hypoplastic left heart syndrome. Cardiology in the Young. 29(12). 1510–1516. 3 indexed citations
15.
Goodfellow, Sebastian D., Andrew Goodwin, Robert Greer, et al.. (2018). Towards Understanding ECG Rhythm Classification Using Convolutional Neural Networks and Attention Mappings. 83–101. 31 indexed citations
16.
Tonekaboni, Sana, Mjaye Mazwi, Peter C. Laussen, et al.. (2018). Prediction of Cardiac Arrest from Physiological Signals in the Pediatric ICU. 534–550. 15 indexed citations
17.
Costello, John M., Michael C. Mongé, Kevin D. Hill, et al.. (2018). Associations Between Unplanned Cardiac Reinterventions and Outcomes After Pediatric Cardiac Operations. The Annals of Thoracic Surgery. 105(4). 1255–1263. 18 indexed citations
18.
Mazwi, Mjaye, et al.. (2017). The role of palliative care in critical congenital heart disease. Seminars in Perinatology. 41(2). 128–132. 33 indexed citations
19.
Broomall, Eileen, Mary E. McBride, Barbara J. Deal, et al.. (2016). Posterior Circulation Ischemia or Occlusion in Five Adults With Failing Fontan Circulation. The Annals of Thoracic Surgery. 101(6). 2315–2320. 2 indexed citations
20.

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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