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作者:Harris Papadopoulos , Efthyvoulos Kyriacou , Andrew Nicolaides
来源:[J].Neural Computing and Applications(IF 1.168), 2017, Vol.28 (6), pp.1209-1223
摘要:We propose an approach for providing well-calibrated confidence measures for determining cerebrovascular risk stratification based on characteristics from noninvasive ultrasound imaging of carotid plaques. An important challenge we address is the class imbalance problem inherent ...
作者:Andrew Nicolaides , John R. Laird ...
来源:[J].Medical & Biological Engineering & Computing(IF 1.79), 2017, Vol.55 (8), pp.1415-1434
摘要:Monitoring of cerebrovascular diseases via carotid ultrasound has started to become a routine. The measurement of image-based lumen diameter (LD) or inter-adventitial diameter (IAD) is a promising approach for quantification of the degree of stenosis. The manual measurements...
作者:Andrew Nicolaides , Shoaib Shafique ...
来源:[J].Journal of Medical Systems(IF 1.783), 2017, Vol.41 (6)
摘要:Severe atherosclerosis disease in carotid arteries causes stenosis which in turn leads to stroke. Machine learning systems have been previously developed for plaque wall risk assessment using morphology-based characterization. The fundamental assumption in such systems is the ext...
作者:... Ajay Gupta , Andrew Nicolaides , Jasjit S. Suri
来源:[J].Computers in Biology and Medicine(IF 1.162), 2017, Vol.91, pp.306-317
摘要:Abstract(#br)Background(#br)This pilot study presents a completely automated, novel, smart, cloud-based, point-of-care system for (a) carotid lumen diameter (LD); (b) stenosis severity index (SSI) and (c) total lumen area (TLA) measurement using B-mode ultrasound. The propos...
作者:... Narendra N. Khanna , Andrew Nicolaides , Jasjit S. Suri
来源:[J].Computers in Biology and Medicine(IF 1.162), 2018, Vol.98, pp.100-117
摘要:Abstract(#br)Motivation(#br)The carotid intima-media thickness (cIMT) is an important biomarker for cardiovascular diseases and stroke monitoring. This study presents an intelligence-based, novel, robust, and clinically-strong strategy that uses a combination of deep-learnin...
作者:Andrew Nicolaides , Ajay Gupta
来源:[J].European Journal of Radiology(IF 2.512), 2019, Vol.114, pp.14-24
摘要:Abstract(#br)The advent of Deep Learning (DL) is poised to dramatically change the delivery of healthcare in the near future. Not only has DL profoundly affected the healthcare industry it has also influenced global businesses. Within a span of very few years, advances such as se...
作者:... John R. Laird , Andrew Nicolaides , Jasjit S. Suri
来源:[J].Computer Methods and Programs in Biomedicine(IF 1.555), 2017, Vol.141, pp.73-81
摘要:Abstract(#br)Background and objectives(#br)Standardization of the carotid IMT requires a reference marker in ultrasound scans. It has been shown previously that manual reference marker and manually created carotid segments are used for measuring IMT in these segments. Manual...
作者:Andrew Nicolaides , Shoaib Shafique ...
来源:[J].Computers in Biology and Medicine(IF 1.162), 2017, Vol.80, pp.77-96
摘要:Abstract(#br)Stroke risk stratification based on grayscale morphology of the ultrasound carotid wall has recently been shown to have a promise in classification of high risk versus low risk plaque or symptomatic versus asymptomatic plaques. In previous studies, this stratificatio...
作者:Andrew Nicolaides , Tadashi Araki ...
来源:[J].Computers in Biology and Medicine(IF 1.162), 2019, Vol.105, pp.125-143
摘要:Abstract(#br)Motivation(#br)AtheroEdge Composite Risk Score (AECRS1.0 10yr ) is an integrated stroke/cardiovascular risk calculator that was recently developed and computes the 10-year risk of carotid image phenotypes by integrating conventional cardiovascular risk factors (CCVRF...
作者:Andrew Nicolaides , Aditya Sharma ...
来源:[J].Computers in Biology and Medicine(IF 1.162), 2019, Vol.108, pp.182-195
摘要:Abstract(#br)Purpose(#br)Conventional cardiovascular risk factors (CCVRFs) and carotid ultrasound image-based phenotypes (CUSIP) are independently associated with long-term risk of cardiovascular (CV) disease. In this study, 26 cardiovascular risk (CVR) factors which consisted of...

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