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Mahdi Tabassian
Mahdi Tabassian
Ph.D., Associate Principal Scientist at MSD
Verified email at msd.com
Title
Cited by
Cited by
Year
Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation (PRIME): A Checklist: Reviewed by the American College of Cardiology Healthcare Innovation …
PP Sengupta, S Shrestha, B Berthon, E Messas, E Donal, GH Tison, ...
Cardiovascular Imaging 13 (9), 2017-2035, 2020
1362020
Diagnosis of heart failure with preserved ejection fraction: machine learning of spatiotemporal variations in left ventricular deformation
M Tabassian, I Sunderji, T Erdei, S Sanchez-Martinez, A Degiovanni, ...
Journal of the American society of echocardiography 31 (12), 1272-1284. e9, 2018
1072018
Statistical shape modeling of the left ventricle: myocardial infarct classification challenge
A Suinesiaputra, P Ablin, X Alba, M Alessandrini, J Allen, W Bai, S Cimen, ...
IEEE journal of biomedical and health informatics 22 (2), 503-515, 2017
872017
Knitted fabric defect classification for uncertain labels based on Dempster–Shafer theory of evidence
M Tabassian, R Ghaderi, R Ebrahimpour
Expert Systems with Applications 38 (5), 5259-5267, 2011
502011
Combining complementary information sources in the Dempster–Shafer framework for solving classification problems with imperfect labels
M Tabassian, R Ghaderi, R Ebrahimpour
Knowledge-Based Systems 27, 92-102, 2012
352012
Machine learning of the spatio-temporal characteristics of echocardiographic deformation curves for infarct classification
M Tabassian, M Alessandrini, L Herbots, O Mirea, ED Pagourelias, ...
The international journal of cardiovascular imaging 33, 1159-1167, 2017
322017
Combination of multiple diverse classifiers using belief functions for handling data with imperfect labels
M Tabassian, R Ghaderi, R Ebrahimpour
Expert systems with applications 39 (2), 1698-1707, 2012
302012
Using artificial intelligence to manage thrombosis research, diagnosis, and clinical management
A Mishra, MZ Ashraf
Seminars in thrombosis and hemostasis 46 (04), 410-418, 2020
162020
Area of the pressure-strain loop during ejection as non-invasive index of left ventricular performance: a population study
N Cauwenberghs, M Tabassian, L Thijs, WY Yang, FF Wei, P Claus, ...
Cardiovascular ultrasound 17, 1-11, 2019
162019
Biventricular imaging markers to predict outcomes in non‐compaction cardiomyopathy: a machine learning study
C Rocon, M Tabassian, M Dantas Tavares de Melo, ...
ESC HEART FAILURE 7, 2431–2439, 2020
12*2020
Proposed requirements for cardiovascular imaging-related machine learning evaluation (PRIME): a checklist: reviewed by the American College of Cardiology Healthcare Innovation …
PP Sengupta, S Shrestha, B Berthon, E Messas, E Donal, GH Tison, ...
Epub 2020/09/12. https://doi. org/10.1016/j. jcmg. 2020.07. 015 PMID …, 0
12
Handling missing strain (rate) curves using K-nearest neighbor imputation
M Tabassian, M Alessandrini, R Jasaityte, L De Marchi, G Masetti, ...
2016 IEEE International Ultrasonics Symposium (IUS), 1-4, 2016
112016
Clutter filtering using a 3D deep convolutional neural network
M Tabassian, XR Hu, B Chakraborty, J D’hooge
2019 IEEE International Ultrasonics Symposium (IUS), 2114-2117, 2019
92019
3D convolutional neural network for segmentation of the urethra in volumetric ultrasound of the pelvic floor
H Williams, L Cattani, W Li, M Tabassian, T Vercauteren, J Deprest, ...
2019 IEEE International Ultrasonics Symposium (IUS), 1473-1476, 2019
82019
Principal component analysis for the classification of cardiac motion abnormalities based on echocardiographic strain and strain rate imaging
M Tabassian, M Alessandrini, L De Marchi, G Masetti, N Cauwenberghs, ...
Functional Imaging and Modeling of the Heart: 8th International Conference …, 2015
82015
Automatic detection of myocardial infarction through a global shape feature based on local statistical modeling
M Tabassian, M Alessandrini, P Claes, L De Marchi, D Vandermeulen, ...
Statistical Atlases and Computational Models of the Heart. Imaging and …, 2016
52016
Automatic detection of ischemic myocardium by spatio-temporal analysis of echocardiographic strain and strain rate curves
M Tabassian, M Alessandrini, L Herbots, O Mirea, J Engvall, L De Marchi, ...
2015 IEEE International Ultrasonics Symposium (IUS), 1-4, 2015
42015
Non-rigid image registration using a modified fuzzy feature-based inference system for 3D cardiac motion estimation
MS Hosseini, MH Moradi, M Tabassian, J D'hooge
Computer Methods and Programs in Biomedicine 205, 106085, 2021
32021
Machine learning for quality assurance of myocardial strain curves
M Tabassian, O ZulaicaIglesias, S Ünlü, JU Voigt, J D'hooge
2018 IEEE International Ultrasonics Symposium (IUS), 1-4, 2018
32018
Handling classification problems with imperfect labels using an evidence-based neural network ensemble
M Tabassian, R Ghaderi, R Ebrahimpour
International Journal of Innovative Computing, Information and Control 7 (12 …, 2011
32011
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Articles 1–20