Yu-Hui Chang

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Social annotation has become a popular manner for web users to manage and share their information and interests. While users' interests vary with time, tag correlation also changes from users' perspectives. In this work, we explore four methods for estimating temporal correlation between social tags and detect if a long term trend emerges from the history(More)
New onset diabetes after transplantation (NODAT) occurs less frequently in living donor liver transplant (LDLT) recipients than in deceased donor liver transplant (DDLT) recipients. The aim of this study was to compare the incidence and predictive factors for NODAT in LDLT versus DDLT recipients. The Organ Procurement and Transplant Network/United Network(More)
This thesis is motivated by a study in which healthy volunteers were inocu-lated with different doses of nontypeable Haemophilus influenzae. The goal was to estimate the doses at which 50% and 90% of subjects became colonized, and these doses are denoted as the HCD50 and HCD90 respectively. A fifteen-subject study was designed in two stages, with the first(More)
UNLABELLED This study analyzed patient adoption of secure messaging to update medication list in an ambulatory care setting. The objective was to establish demographic differences between users and non-users of secure messaging for medications list update. Efficiency of secure messaging for the updates was compared to fax and telephone based updates. (More)
BACKGROUND Although the use of a physician and nurse team at triage has been shown to improve emergency department (ED) throughput, the mechanism(s) by which these improvements occur is less clear. OBJECTIVES 1) To describe the effect of a Rapid Medical Assessment (RMA) team on ED length of stay (LOS) and rate of left without being seen (LWBS); 2) To(More)
OBJECTIVE Identification of patients at high risk for new-onset diabetes after kidney transplantation (NODAT) will facilitate clinical trials for its prevention. RESEARCH DESIGN AND METHODS We previously described a pretransplant predictive risk model for NODAT using seven pretransplant variables (age, planned use of maintenance corticosteroids,(More)
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