Titlebook: 6th Kuala Lumpur International Conference on Biomedical Engineering 2021; Proceedings of BioMe Juliana Usman,Yih Miin Liew,Fatimah Ibrahim

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Wissenschaftliche Kongresse und Preise, high and low stenosis degrees. Analysis of the I. factor revealed that the Carreau model represented blood viscosity more appropriately by exhibiting both Newtonian and non-Newtonian behavior of blood in both healthy and diseased arteries. Extensive analysis of the concerned parameters demonstrated

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Lehre, Fort- und Weiterbildung,ariation was also observed in LVH patients, especially near the region with wall thickening and distinct local wall curvature. A high convexity area was observed to have high circumferential stress and low longitudinal stress, while the opposite was noted at the local high concavity area. These find

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Lehre, Fort- und Weiterbildung,contrary, 6.55% of the aneurysm shows OSI values higher than 0.45 for the HB model, and the area percentage is 6.72% for the Newtonian model. Three different viscous models showed that viscous models influence the outcome of computational analyses to a great extent, and an appropriate viscous model

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CHYME

Lehre, Fort- und Weiterbildung,ssment by applying the k-Means clustering algorithm classifies the medical equipment into three priority levels. The corrective maintenance prioritization assessment system can assist the clinical engineers in managing the rectification expenditure, reporting, preparation, workforce, and material. T

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Wissenschaftliche Kongresse und Preise,gression analysis. The results revealed that the developed model based on combination of KOA X-ray key features and patient assessment data is able to predict the severity of KOA with high level of accuracy (89.2%) and acceptable level of inter-rater reliability with quadratic weighted Cohen’s Kappa

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https://doi.org/10.1007/978-3-642-93718-7plaque as they are much more prominent to be labelled manually. The image dataset was pre-processed with Gabor filters before training the Random Forest (RF) and XGBoost models. The results demonstrated that the XGBoost model performed slightly better than the Random Forest model with 82.0% and 80.9

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