The availability of data for the size of the “underground economy” (UE) is important for macroeconomic policy. We use fuzzy set theory and fuzzy logic to construct an annual time-series for the (unobservable) New Zealand UE over the period 1968–1994. Two input variables are used—the effective tax rate and an index of the degree of regulation (REG). The resulting UE time-series is compared with ...

We present a method for identifying errors in EHRs caused by copying and pasting text containing relative dates. Our method utilizes a sequence alignment method for recognizing instances of copy/paste, and regular expressions for relative dates. We furthermore present an analysis of our method on the MIMIC-II dataset. Introduction Electronic health records (EHR) are a powerful enabling technolo...

This paper considers an MIG/c queueing system serving a finite number (J) of distinct customer classes. Performance of the system, as measured by the vector of steady-state xpected waiting times of the customer classes (the performance vector), may be controlled by adopting an appropriate priority discipline. We show that the performance space, the set of performance vectors which are achievabl...

The study of Latino public opinion has renewed interest in the relationship between language and survey response. However, extant research generally relies on statistical methods that cannot distinguish between two related yet distinct types of language effects in Latino surveys: (1) differences in attitude and (2) differences in measures of attitude. The former reflects varied levels of a late...

This project focuses on characterizing intravenous (IV) medication administration in an intensive care unit at a partner hospital. Information regarding IV medication dose was extracted from MIMIC II, a large database containing real patient data; this information was used to characterize the use of twelve hemodynamic drugs. Characterization was performed by extracting features such as maximum ...

Most of the existing medicine recommendation systems that are mainly based on electronic medical records (EMRs) are significantly assisting doctors to make better clinical decisions benefiting both patients and caregivers. Even though the growth of EMRs is at a lighting fast speed in the era of big data, content limitations in EMRs restrain the existed recommendation systems to reflect relevant...

We present a model-based monitoring method for dynamic systems that exhibit both discrete and continuous behaviors. MIMIC [Dvorak and Kuipers, 1991] uses qualitative and semiquantitative models to monitor dynamic systems even with incomplete knowledge. Recent advances have improved the quality of semi-quantitative behavior predictions, used observations to refine static envelopes around monoton...

This project focuses on characterizing intravenous (IV) medication administration in an intensive care unit at a partner hospital. Information regarding IV medication dose was extracted from MIMIC II, a large database containing real patient data; this information was used to characterize the use of twelve hemodynamic drugs. Characterization was performed by extracting features such as maximum ...

We describe the framework of a data-fuelled, interdisciplinary team-led learning system. The idea is to build models using patients from one's own institution whose features are similar to an index patient as regards an outcome of interest, in order to predict the utility of diagnostic tests and interventions, as well as inform prognosis. The Laboratory of Computational Physiology at the Massac...