Business process modeling for software acquisition - A literature review

Los Alamitos, US

Split private and shared L2 cache architecture for snooping-based CMP

California, US

Analysing homogenous patient journeys to assess quality of care for patients admitted outside of their ‘home-ward’

This study is the first to explore the quality of care based on the outlier or the inlier status of patients for a large heterogeneous General Medicine (GM) service at a busy public hospital. The study compared the quality of care between ward outliers and ward inliers based on a homogenous group of patients using Two-step clustering method. Contrary to common perception, ward outliers had overall shorter Length of Stay (LOS) than ward inliers. The study also was unable to support the perception of shorter LOS in the outlier group being associated with higher in-hospital mortality. The study confirmed that overall the outliers received inferior quality of care as discharge summaries for the outliers were delayed and more outliers were re-admitted within 7 days of discharge in comparison to the inliers

Gaining insight from patient journey data using process-oriented analysis approach

Hospitals are continually struggling to cater for the increasing demand for inpatient services. This is due to increased population, aging, and the rising incidence of chronic diseases associated with modern life. The high demand for hospital services leads to unpredictable bed availability, longer waiting period for acute admission, difficulties in keeping planned admission, stressed hospital staff, undesirable patient and family experience, as well as unclear long term impact on health care capacity. This study aims to derive some correlation between various factors contributing to ward occupancy rate and operation efficiency. The aim is also to discover the inpatient flow process model proposing to use process mining techniques combined with data analysis to depict the relationships among inpatients, wards and Length of Stay (LOS) in an effort to gain insight into factors that could be focused to relieve access block. Open source process mining software - ProM is used for this study. The study is done in collaboration with Flinders Medical Centre (FMC) using data from their Patient Journey Database as case study

Hypergraph Convolutional Networks for Fine-grained ICU Patient Similarity Analysis and Risk Prediction

The Intensive Care Unit (ICU) is one of the most important parts of a hospital, which admits critically ill patients and provides continuous monitoring and treatment. Various patient outcome prediction methods have been attempted to assist healthcare professionals in clinical decision-making. Existing methods focus on measuring the similarity between patients using deep neural networks to capture the hidden feature structures. However, the higher-order relationships are ignored, such as patient characteristics (e.g., diagnosis codes) and their causal effects on downstream clinical predictions. In this paper, we propose a novel Hypergraph Convolutional Network that allows the representation of non-pairwise relationships among diagnosis codes in a hypergraph to capture the hidden feature structures so that fine-grained patient similarity can be calculated for personalized mortality risk prediction. Evaluation using a publicly available eICU Collaborative Research Database indicates that our method achieves superior performance over the state-of-the-art models on mortality risk prediction. Moreover, the results of several case studies demonstrated the effectiveness of constructing graph networks in providing good transparency and robustness in decision-making.Comment: 7 pages, 2 figures, submitted to IEEE BIBM 202

Fish Cholesterol 25-Hydroxylase Inhibits Virus Replication via Regulating Interferon Immune Response or Affecting Virus Entry

Cholesterol 25-hydroxylase (CH25H) is an interferon (IFN)-induced gene that catalyzes the oxidation of cholesterol to 25-hydroxycholesterol (25HC), which exerts broad-spectrum antiviral function. To investigate the roles of fish CH25H in Singapore grouper iridovirus (SGIV) and red-spotted grouper nervous necrosis virus (RGNNV) infection, we cloned and characterized a CH25H homolog from orange-spotted grouper (Epinephelus coioides) (EcCH25H). EcCH25H encoded a 271-amino-acid polypeptide, with 86 and 59% homology with yellow croaker (Larimichthys crocea) and humans, respectively. EcCH25H contained a conserved fatty acid (FA) hydroxylase domain and an ERG3 domain. EcCH25H expression was induced by RGNNV or SGIV infection, lipopolysaccharide (LPS) or poly (I:C) treatment in vitro. Subcellular localization showed that EcCH25H and mutant EcCH25H-M were distributed in the cytoplasm and partly colocalized with the endoplasmic reticulum. SGIV and RGNNV replication was decreased by EcCH25H overexpression, which was reflected in the reduced severity of the cytopathic effect and a decrease in viral gene transcription, but replication of both viruses was increased by knockdown of EcCH25H. Besides, the antiviral activity was dependent on its enzymatic activity. Treatment with 25HC significantly inhibited replication of SGIV and RGNNV. EcCH25H overexpression positively regulated the IFN-related molecules and proinflammatory cytokines, and increased both IFN and ISRE promoter activities. Moreover, 25HC treatment significantly suppressed SGIV and RGNNV entry into host cells. The similar inhibitory effect on SGIV entry was observed in EcCH25H overexpression cells. Taken together, our findings demonstrated that EcCH25H inhibited SGIV and RGNNV infection by regulating IFN signaling molecules, and might also influence viral entry via an effect on cholesterol

Implementing process change in a software organization - an experience based study

Heidelber