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Abstract: To assist managers in monitoring the progress of their IT programs, we propose a Bayesian Network stochastic model, the IT Decision Management System (ITDMS), to simulate the program's evidence observations, complex interrelationships, and the dynamic/temporal relationships. Based on the Information Technology Infrastructure Library (ITIL)®1 The model aligns the sub‐process of each ITIL Phase in a Bayesian structure measuring status to provide the decision maker a measurement of the likelihood of program success. [ABSTRACT FROM AUTHOR]

Dynamic asset allocation in financial investment with an optimal equity growth principle based on mutual information in communication theory is considered. Specifically, the asset allocation formula using Kelly's criteria derived from channel capacity of a binary symmetric channel is developed. The goal is to determine the optimal fraction of equity to be invested between a risk-free asset and a risky asset in a repeated trading activity. The analytical operating curve to predict trading performance is provided. An extension for dynamic multi-asset allocation is also presented. An out-of-sample simulation based on historical market data demonstrates the effectiveness of the methodology. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the characteristics of gynecologic cancer patients visiting the emergency department (ED). Materials and Methods: A retrospective cohort of gynecologic cancer patients in ED visits from 2000 to 2012 was analyzed using the Longitudinal Health Insurance Database 2000 (LHID2000) which randomly selected 1,000,000 beneficiaries from the year 2000 Registry of Beneficiaries (n = 23.72 million). Results: There were 5,893 ED visits by 1,400 gynecologic cancer patients. The mean age was 55.22 ± 14.60 years. The mean number of ED visits was 4.21±5.18. 657 (46.93%) patients that were admitted to hospital; 70.57% ED visits occurred in medical center. Abdominal pain (19.04%), complications of surgical and medical care (13.28%) and intestinal obstruction without mention of hernia (10.69%) are the most three common presenting symptoms except other symptoms, signs, and ill-defined conditions (24.79%); 62.56% of the medications prescribed in ED visits are of gastrointestinal category. The overall survival rate of ED visits was significantly lower than that of no ED visits (p < 0.0001). Conclusions: Relatively low rate of hospital admission may indicate unnecessary ED visits resulting in healthcare costs. Abdominal pain is the most common specific symptoms at presentation. Most medications belong to the gastrointestinal category reminding us of the importance of nutrition support. ED visits were a significant poor prognostic factor for overall survival. [ABSTRACT FROM AUTHOR]

Value-at-Risk (VaR) is a well-accepted risk metric in modern quantitative risk management (QRM). The classical Monte Carlo simulation (MCS) approach, denoted henceforth as the classical approach, assumes the independence of loss severity and loss frequency. In practice, this assumption does not always hold true. Through mathematical analyses, we show that the classical approach is prone to significant biases when the independence assumption is violated. This is also corroborated by studying both simulated and real-world datasets. To overcome the limitations and to more accurately estimate VaR, we develop and implement the following two approaches for VaR estimation: the data-driven partitioning of frequency and severity (DPFS) using clustering analysis, and copula-based parametric modeling of frequency and severity (CPFS). These two approaches are verified using simulation experiments on synthetic data and validated on five publicly available datasets from diverse domains; namely, the financial indices data of Standard & Poor's 500 and the Dow Jones industrial average, chemical loss spills as tracked by the US Coast Guard, Australian automobile accidents, and US hurricane losses. The classical approach estimates VaR inaccurately for 80% of the simulated data sets and for 60% of the real-world data sets studied in this work. Both the DPFS and the CPFS methodologies attain VaR estimates within 99% bootstrap confidence interval bounds for both simulated and real-world data. We provide a process flowchart for risk practitioners describing the steps for using the DPFS versus the CPFS methodology for VaR estimation in real-world loss datasets. [ABSTRACT FROM AUTHOR]

This paper describes a continuous-time state-process, discretetime observation, Interacting Multiple Model (IMM) tracking algorithm, and its applications to financial market modeling and asset allocation. The system state is modeled as a continuous-time, affine-Gaussian stochastic dynamical process driven by a white process noise, as well as by structural changes modeled by a finitestate, continuous-time, Markov process. The system generally assumes multiple models with different state space dimensions and an affine-Gaussian state jump whenever a model transition occurs. The underlying problem is a standard filtering problem for estimating the system state based on a sequence of discrete-time, linear- Gaussian observations of partial system states. To demonstrate the new method, we apply the IMM algorithm to financial market modeling for dynamic asset allocation. The resulting performance shows the potential applicability of the proposed method. [ABSTRACT FROM AUTHOR]

Background and purpose: Fabry disease is an X‐linked disease, and enzyme‐based screening methods are not suitable for female patients. Methods: In total, 1000 young stroke patients (18–55 years, 661 with ischaemic stroke and 339 with hypertensive intracerebral hemorrhage) were recruited. The Sequenom iPLEX assay was used to detect 26 Fabry related mutation genes. The frequency of Fabry disease in young stroke was reviewed and compared between Asian and non‐Asian countries. Results: Two male patients with ischaemic stroke were found to have a genetic mutation of IVS4+919G>A. There was no α‐galactosidase A (GLA) gene mutation in female patients. The frequency in Asian stroke patients was 0.62% (male vs. female 0.63% vs. 0.58%) with 0.72% for ischaemic stroke and none for hemorrhagic stroke, compared to 0.88% (0.77% vs. 1.08%) with 0.83% for ischaemic stroke and 1.40% for hemorrhagic stroke reported in western countries. Conclusion: IVS4+919G>A is the GLA mutation in Taiwanese young ischaemic stroke patients. Fabry disease is more frequent among non‐Asian patients compared to Asian patients. [ABSTRACT FROM AUTHOR]