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Damini Dey
Damini Dey
Biomedical Imaging Research Institute, Cedars-Sinai Medical Center
Verified email at cshs.org
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Cited by
Cited by
Year
Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis
M Motwani, D Dey, DS Berman, G Germano, S Achenbach, MH Al-Mallah, ...
European heart journal 38 (7), 500-507, 2017
6692017
Artificial Intelligence in Cardiovascular Imaging: JACC State-of-the-Art Review
D Dey, PJ Slomka, P Leeson, D Comaniciu, S Shrestha, PP Sengupta, ...
Journal of the American College of Cardiology 73 (11), 1317-1335, 2019
4712019
Low-attenuation noncalcified plaque on coronary computed tomography angiography predicts myocardial infarction: results from the multicenter SCOT-HEART trial (Scottish Computed …
MC Williams, J Kwiecinski, M Doris, P McElhinney, MS D’Souza, S Cadet, ...
Circulation 141 (18), 1452-1462, 2020
3922020
Deep learning for prediction of obstructive disease from fast myocardial perfusion SPECT: a multicenter study
J Betancur, F Commandeur, M Motlagh, T Sharir, AJ Einstein, S Bokhari, ...
JACC: Cardiovascular Imaging 11 (11), 1654-1663, 2018
3092018
Pericardial fat burden on ECG-gated noncontrast CT in asymptomatic patients who subsequently experience adverse cardiovascular events
VY Cheng, D Dey, B Tamarappoo, R Nakazato, H Gransar, ...
JACC: Cardiovascular Imaging 3 (4), 352-360, 2010
2932010
Increased volume of epicardial fat is an independent risk factor for accelerated progression of sub-clinical coronary atherosclerosis
A Yerramasu, D Dey, S Venuraju, DV Anand, S Atwal, R Corder, ...
Atherosclerosis 220 (1), 223-230, 2012
2912012
Coronary plaque quantification and fractional flow reserve by coronary computed tomography angiography identify ischaemia-causing lesions
S Gaur, KA Øvrehus, D Dey, J Leipsic, HE Bøtker, JM Jensen, J Narula, ...
European heart journal 37 (15), 1220-1227, 2016
2872016
Automated three-dimensional quantification of noncalcified coronary plaque from coronary CT angiography: comparison with intravascular US
D Dey, T Schepis, M Marwan, PJ Slomka, DS Berman, S Achenbach
Radiology 257 (2), 516-522, 2010
2142010
Pericoronary adipose tissue computed tomography attenuation and high-risk plaque characteristics in acute coronary syndrome compared with stable coronary artery disease
M Goeller, S Achenbach, S Cadet, AC Kwan, F Commandeur, PJ Slomka, ...
JAMA cardiology 3 (9), 858-863, 2018
2072018
Prognostic value of combined clinical and myocardial perfusion imaging data using machine learning
J Betancur, Y Otaki, M Motwani, MB Fish, M Lemley, D Dey, H Gransar, ...
JACC: Cardiovascular Imaging 11 (7), 1000-1009, 2018
1982018
Computer-aided non-contrast CT-based quantification of pericardial and thoracic fat and their associations with coronary calcium and metabolic syndrome
D Dey, ND Wong, B Tamarappoo, R Nakazato, H Gransar, VY Cheng, ...
Atherosclerosis 209 (1), 136-141, 2010
1802010
Deep learning for quantification of epicardial and thoracic adipose tissue from non-contrast CT
F Commandeur, M Goeller, J Betancur, S Cadet, M Doris, X Chen, ...
IEEE transactions on medical imaging 37 (8), 1835-1846, 2018
1762018
Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjects
M Goeller, S Achenbach, M Marwan, MK Doris, S Cadet, F Commandeur, ...
Journal of cardiovascular computed tomography 12 (1), 67-73, 2018
1762018
Integrated prediction of lesion-specific ischaemia from quantitative coronary CT angiography using machine learning: a multicentre study
D Dey, S Gaur, KA Ovrehus, PJ Slomka, J Betancur, M Goeller, MM Hell, ...
European radiology 28, 2655-2664, 2018
1692018
Increased pericardial fat volume measured from noncontrast CT predicts myocardial ischemia by SPECT
B Tamarappoo, D Dey, H Shmilovich, R Nakazato, H Gransar, VY Cheng, ...
JACC: Cardiovascular Imaging 3 (11), 1104-1112, 2010
1672010
Relationship between changes in pericoronary adipose tissue attenuation and coronary plaque burden quantified from coronary computed tomography angiography
M Goeller, BK Tamarappoo, AC Kwan, S Cadet, F Commandeur, ...
European Heart Journal-Cardiovascular Imaging 20 (6), 636-643, 2019
1492019
Peri-Coronary Adipose Tissue Density Is Associated With 18F-Sodium Fluoride Coronary Uptake in Stable Patients With High-Risk Plaques
J Kwiecinski, D Dey, S Cadet, SE Lee, Y Otaki, PT Huynh, MK Doris, ...
JACC: Cardiovascular Imaging 12 (10), 2000-2010, 2019
1402019
Improved accuracy of myocardial perfusion SPECT for detection of coronary artery disease by machine learning in a large population
R Arsanjani, Y Xu, D Dey, V Vahistha, A Shalev, R Nakanishi, S Hayes, ...
Journal of Nuclear Cardiology 20 (4), 553-562, 2013
1392013
Impact of family history of coronary artery disease in young individuals (from the CONFIRM registry)
Y Otaki, H Gransar, DS Berman, VY Cheng, D Dey, FY Lin, S Achenbach, ...
The American journal of cardiology 111 (8), 1081-1086, 2013
1332013
Prediction of revascularization after myocardial perfusion SPECT by machine learning in a large population
R Arsanjani, D Dey, T Khachatryan, A Shalev, SW Hayes, M Fish, ...
Journal of Nuclear Cardiology 22 (5), 877-884, 2015
1302015
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