Zobrazeno 1 - 10
of 570
pro vyhledávání: '"Hoori, A."'
Autor:
Wu, Hao, Song, Yingnan, Hoori, Ammar, Subramaniam, Ananya, Lee, Juhwan, Kim, Justin, Hu, Tao, Al-Kindi, Sadeer, Huang, Wei-Ming, Yun, Chun-Ho, Hung, Chung-Lieh, Rajagopalan, Sanjay, Wilson, David L.
We assessed the benefit of combining stress cardiac CT perfusion (CCTP) myocardial blood flow (MBF) with coronary CT angiography (CCTA) using our innovative CCTP software. By combining CCTA and CCTP, one can uniquely identify a flow limiting stenosis
Externí odkaz:
http://arxiv.org/abs/2401.17433
Autor:
Hu, Tao, Freeze, Joshua, Singh, Prerna, Kim, Justin, Song, Yingnan, Wu, Hao, Lee, Juhwan, Al-Kindi, Sadeer, Rajagopalan, Sanjay, Wilson, David L., Hoori, Ammar
Background: Recent studies have used basic epicardial adipose tissue (EAT) assessments (e.g., volume and mean HU) to predict risk of atherosclerosis-related, major adverse cardiovascular events (MACE). Objectives: Create novel, hand-crafted EAT featu
Externí odkaz:
http://arxiv.org/abs/2401.16190
Autor:
Song, Yingnan, Wu, Hao, Lee, Juhwan, Kim, Justin, Hoori, Ammar, Hu, Tao, Zimin, Vladislav, Makhlouf, Mohamed, Al-Kindi, Sadeer, Rajagopalan, Sanjay, Yun, Chun-Ho, Hung, Chung-Lieh, Wilson, David L.
We investigated the feasibility and advantages of using non-contrast CT calcium score (CTCS) images to assess pericoronary adipose tissue (PCAT) and its association with major adverse cardiovascular events (MACE). PCAT features from coronary CTA (CCT
Externí odkaz:
http://arxiv.org/abs/2401.15554
Autor:
Rafieian, Hoori (AUTHOR) hrafieiankoopaei@fordham.edu, Huang, Yanliu (AUTHOR), Kahn, Barbara E (AUTHOR)
Publikováno v:
Journal of Consumer Research. Apr2024, Vol. 50 Issue 6, p1157-1171. 15p.
Autor:
Lee, Juhwan, Kim, Justin N., Dallan, Luis A. P., Zimin, Vladislav N., Hoori, Ammar, Hassani, Neda S., Makhlouf, Mohamed H. E., Guagliumi, Giulio, Bezerra, Hiram G., Wilson, David L.
Thin-cap fibroatheroma (TCFA) is a prominent risk factor for plaque rupture. Intravascular optical coherence tomography (IVOCT) enables identification of fibrous cap (FC), measurement of FC thicknesses, and assessment of plaque vulnerability. We deve
Externí odkaz:
http://arxiv.org/abs/2311.06202
Publikováno v:
Journal of Service Management, 2024, Vol. 35, Issue 4, pp. 547-569.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JOSM-12-2023-0510
Autor:
Hoori, Ammar, Al-Kindi, Sadeer, Hu, Tao, Song, Yingnan, Wu, Hao, Lee, Juhwan, Tashtish, Nour, Fu, Pingfu, Gilkeson, Robert, Rajagopalan, Sanjay, Wilson, David L.
Background. Coronary artery calcium (CAC) is a powerful predictor of major adverse cardiovascular events (MACE). Traditional Agatston score simply sums the calcium, albeit in a non-linear way, leaving room for improved calcification assessments that
Externí odkaz:
http://arxiv.org/abs/2308.12224
Autor:
Wu, Hao, Song, Yingnan, Hoori, Ammar, Subramaniam, Ananya, Lee, Juhwan, Kim, Justin, Hu, Tao, Al-Kindi, Sadeer, Huang, Wei-Ming, Yun, Chun-Ho, Hung, Chung-Lieh, Rajagopalan, Sanjay, Wilson, David L.
Features of pericoronary adipose tissue (PCAT) assessed from coronary computed tomography angiography (CCTA) are associated with inflammation and cardiovascular risk. As PCAT is vascularly connected with coronary vasculature, the presence of iodine i
Externí odkaz:
http://arxiv.org/abs/2306.15593
Autor:
Ammar Hoori, Sadeer Al-Kindi, Tao Hu, Yingnan Song, Hao Wu, Juhwan Lee, Nour Tashtish, Pingfu Fu, Robert Gilkeson, Sanjay Rajagopalan, David L. Wilson
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Whole-heart coronary calcium Agatston score is a well-established predictor of major adverse cardiovascular events (MACE), but it does not account for individual calcification features related to the pathophysiology of the disease (e.g., mul
Externí odkaz:
https://doaj.org/article/52c409dcb9a544db9e3dcdea6fa8452e
Autor:
Lee, Juhwan, Kim, Justin N., Gomez-Perez, Lia, Gharaibeh, Yazan, Motairek, Issam, Pereira, Ga-briel T. R., Zimin, Vladislav N., Dallan, Luis A. P., Hoori, Ammar, Al-Kindi, Sadeer, Guagliumi, Giulio, Bezerra, Hiram G., Wilson, David L.
To analyze this characteristic of vulnerability, we developed an automated deep learning method for detecting microvessels in intravascular optical coherence tomography (IVOCT) images. A total of 8,403 IVOCT image frames from 85 lesions and 37 normal
Externí odkaz:
http://arxiv.org/abs/2210.00166