Katholieke Universiteit Leuven

About: Katholieke Universiteit Leuven is a education organization based out in Leuven, Belgium. It is known for research contribution in the topics: Population & Context (language use). The organization has 61109 authors who have published 176584 publications receiving 6210872 citations.

Lévy Processes in Finance: Pricing Financial Derivatives

Abstract: Preface. Acknowledgements. Introduction. Financial Mathematics in Continuous Time. The Black-Scholes Model. Imperfections of the Black-Scholes Model. Levy Processes and OU Processes. Stock Price Models Driven by Levy Processes. Levy Models with Stochastic Volatility. Simulation Techniques. Exotic Option Pricing. Interest-Rate Models. Appendix A: Special Functions. Appendix B: Levy Processes. Appendix C: S&P 500 Call Option Prices. References. Index.

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Abstract: Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumoris a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses thestate-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross tota lresection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset.

Outcome benefit of intensive insulin therapy in the critically ill: Insulin dose versus glycemic control.

Abstract: ObjectivesMaintenance of normoglycemia with insulin reduces mortality and morbidity of critically ill patients. Here we report the factors determining insulin requirements and the impact of insulin dose vs. blood glucose control on the observed outcome benefits.DesignA prospective, randomized, contr