Ken Gin

1.6k citations

52 papers · 1.2k · h-index 19

Impact in

Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
Health Information Management top 2%
- Artificial Intelligence in Healthcare

Papers in

Cardiology and Cardiovascular Medicine 34
- Cardiovascular Function and Risk Factors 15
- Atrial Fibrillation Management and Outcomes 5
- Cardiac Valve Diseases and Treatments 5
- ECG Monitoring and Analysis 5
Health Informatics 12
- Artificial Intelligence in Healthcare and Education 12

Co-authors: John Jue (24 shared papers)Teresa S.M. Tsang (36 shared papers)Purang Abolmaesumi (27 shared papers)Robert N. Rohling (19 shared papers)Christina L. Luong (26 shared papers)Amir Hossein Abdi (11 shared papers)Hany Girgis (14 shared papers)Zhibin Liao (8 shared papers)
Journals: Canadian Journal of Cardiology (8 papers)IEEE Transactions on Medical Imaging (5 papers)Journal of the American Society of Echocardiography (4 papers)International Journal of Computer Assisted Radiology and Surgery (2 papers)Critical Care Medicine (1 paper)
Partner nations: Canada United States New Zealand

In The Last Decade

Ken Gin

50 papers receiving 1.2k citations

Peers

Countries citing papers authored by Ken Gin

Since Specialization

Citations

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

Fields of papers citing papers by Ken Gin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ken Gin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ken Gin Line = papers co-authored together Ken Gin links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Echocardiographic Predictors of Survival and Response to Early Revascularization in Cardiogenic Shock Circulation ·Michael H. Picard, Ravin Davidoff, Lynn A. Sleeper, Lisa A. Mendes, Christopher Thompson, Vladimír Džavík, Richard M. Steingart, Ken Gin	2003	120
2	Automatic Quality Assessment of Echocardiograms Using Convolutional Neural Networks: Feasibility on the Apical Four-Chamber View IEEE Transactions on Medical Imaging ·Amir Hossein Abdi, Christina L. Luong, Teresa S.M. Tsang, Saman Nouranian, John Jue, Dale Hawley, Sarah Fleming, Ken Gin	2017	115
3	Diastolic filling in human severe sepsis Critical Care Medicine ·Brad I. Munt, John Jue, Ken Gin, John C. Fenwick, Martin Tweeddale	1998	97
4	The Natural History and Rate of Progression of Aortic Stenosis CHEST Journal ·Steven J. Lester, Brett G. Heilbron, Ken Gin, Arthur Dodek, John Jue	1998	78
5	Cardiac Phase Detection in Echocardiograms With Densely Gated Recurrent Neural Networks and Global Extrema Loss IEEE Transactions on Medical Imaging ·Fatemeh Taheri Dezaki, Zhibin Liao, Christina L. Luong, Hany Girgis, Neeraj Dhungel, Amir Hossein Abdi, Delaram Behnami, Ken Gin	2018	73
6	Precautions and Procedures for Coronary and Structural Cardiac Interventions During the COVID-19 Pandemic: Guidance from Canadian Association of Interventional Cardiology Canadian Journal of Cardiology ·David Alexander Wood, Janar Sathananthan, Ken Gin, Samer Mansour, Hung Q. Ly, Ata-Ur-Rehman Quraishi, Andrea Lavoie, Sohrab R. Lutchmedial	2020	58
7	Outcome of patients aged ≥75 years in the SHould we emergently revascularize Occluded Coronaries in cardiogenic shocK (SHOCK) trial: Do elderly patients with acute myocardial infarction complicated by cardiogenic shock respond differently to emergent revascularization? American Heart Journal ·Vladimír Džavík, Lynn A. Sleeper, Michael H. Picard, Timothy A. Sanborn, April M. Lowe, Ken Gin, Jorge Saucedo, John G. Webb	2005	54
8	Prophylactic Magnesium Does Not Prevent Atrial Fibrillation After Cardiac Surgery: A Meta-Analysis The Annals of Thoracic Surgery ·Richard Cook, Michael H. Yamashita, Mark J. Kearns, Ken Gin, Karin H. Humphries +1 other	2012	48
9	On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra- Observer Variability in 2D Echocardiography Quality Assessment IEEE Transactions on Medical Imaging ·Zhibin Liao, Hany Girgis, Amir Hossein Abdi, Hooman Vaseli, Jorden Hetherington, Robert N. Rohling, Ken Gin, Teresa S.M. Tsang	2019	47
10	Automatic biplane left ventricular ejection fraction estimation with mobile point-of-care ultrasound using multi-task learning and adversarial training International Journal of Computer Assisted Radiology and Surgery ·Mohammad H. Jafari, Hany Girgis, Nathan Van Woudenberg, Zhibin Liao, Robert N. Rohling, Ken Gin, Purang Abolmaesumi, Teresa S.M. Tsang	2019	44
11	Pulmonary effects of low dose amiodarone: a review of the risks and recommendations for surveillance. PubMed ·Rubina Sunderji, Zahra Kanji, Ken Gin	2000	36
12	A Unified Framework Integrating Recurrent Fully-Convolutional Networks and Optical Flow for Segmentation of the Left Ventricle in Echocardiography Data Lecture notes in computer science ·Mohammad H. Jafari, Hany Girgis, Zhibin Liao, Delaram Behnami, Amir Hossein Abdi, Hooman Vaseli, Christina L. Luong, Robert N. Rohling	2018	36
13	Quality Assessment of Echocardiographic Cine Using Recurrent Neural Networks: Feasibility on Five Standard View Planes Lecture notes in computer science ·Amir Hossein Abdi, Christina L. Luong, Teresa S.M. Tsang, John Jue, Ken Gin, Darwin F. Yeung, Dale Hawley, Robert N. Rohling	2017	29
14	Clinical effectiveness of a systematic “pill-in-the-pocket” approach for the management of paroxysmal atrial fibrillation Heart Rhythm ·Jason G. Andrade, Laurent Macle, Ren Jie Robert Yao, Matthew T. Bennett, Christopher B. Fordyce, Nathaniel Mark Hawkins, Andrew David Krahn, John Jue	2018	29
15	Echocardiographic Assessment of Patients with Fabry Disease Journal of the American Society of Echocardiography ·Darwin F. Yeung, Sandra M. Sirrs, Michael Tsang, Ken Gin, Christina L. Luong, John Jue, Pui K. Lee, Teresa S.M. Tsang +1 other	2018	28
16	Cardiac point-of-care to cart-based ultrasound translation using constrained CycleGAN International Journal of Computer Assisted Radiology and Surgery ·Mohammad H. Jafari, Hany Girgis, Nathan Van Woudenberg, Nathaniel Moulson, Christina L. Luong, Andrea Fung, Shane J. T. Balthazaar, John Jue	2020	27
17	Deep Residual Recurrent Neural Networks for Characterisation of Cardiac Cycle Phase from Echocardiograms Lecture notes in computer science ·Fatemeh Taheri Dezaki, Neeraj Dhungel, Amir Hossein Abdi, Christina L. Luong, Teresa S.M. Tsang, John Jue, Ken Gin, Dale Hawley	2017	25
18	Semi-Supervised Learning For Cardiac Left Ventricle Segmentation Using Conditional Deep Generative Models as Prior IEEE International Symposium on Biomedical Imaging (ISBI) ·Mohammad H. Jafari, Hany Girgis, Amir Hossein Abdi, Zhibin Liao, Mehran Pesteie, Robert N. Rohling, Ken Gin, Teresa S.M. Tsang	2019	24
19	Designing lightweight deep learning models for echocardiography view classification SPIE Medical Imaging: Image-Guided Procedures, Robotic Interventions, and Modeling ·Hooman Vaseli, Zhibin Liao, Amir Hossein Abdi, Hany Girgis, Delaram Behnami, Christina L. Luong, Fatemeh Taheri Dezaki, Neeraj Dhungel	2019	23
20	Usefulness of the Atrial Emptying Fraction to Predict Maintenance of Sinus Rhythm After Direct Current Cardioversion for Atrial Fibrillation The American Journal of Cardiology ·Christina L. Luong, Darby J.S. Thompson, Ken Gin, John Jue, Pui-Kee Lee, Michael Y. C. Tsang, Marion E. Barnes, Pamela Colley	2016	19

About Ken Gin

Ken Gin is a scholar working on Cardiology and Cardiovascular Medicine, Health Informatics, Health Information Management, Computer Vision and Pattern Recognition and Critical Care and Intensive Care Medicine, having authored 52 papers that have together received 1.2k indexed citations. Recurring topics across this work include Cardiovascular Function and Risk Factors (15 papers), Artificial Intelligence in Healthcare (14 papers), Artificial Intelligence in Healthcare and Education (12 papers), Medical Image Segmentation Techniques (7 papers), Ultrasound in Clinical Applications (5 papers), Atrial Fibrillation Management and Outcomes (5 papers), Cardiac Valve Diseases and Treatments (5 papers) and ECG Monitoring and Analysis (5 papers). The work is most often cited by research in Health Informatics (266 citations), Health Information Management (201 citations), Cardiology and Cardiovascular Medicine (535 citations), Critical Care and Intensive Care Medicine (67 citations) and Computer Vision and Pattern Recognition (284 citations). Ken Gin has collaborated with scholars based in Canada, United States and New Zealand. Frequent co-authors include John Jue, Teresa S.M. Tsang, Purang Abolmaesumi, Robert N. Rohling, Christina L. Luong, Amir Hossein Abdi, Hany Girgis, Zhibin Liao, Brad I. Munt and Rubina Sunderji. Their work appears in journals such as Canadian Journal of Cardiology, IEEE Transactions on Medical Imaging, Journal of the American Society of Echocardiography, International Journal of Computer Assisted Radiology and Surgery and Critical Care Medicine.

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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