Artur Akbarov

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Forecasting the number of warranty claims is vitally important for manufacturers/warranty providers in preparing fiscal plans. In existing literature, a number of techniques such as log-linear Poisson models, Kalman filter, time series models, and artificial neural network models have been developed. Nevertheless, one might find two weaknesses existing in(More)
Forecasting warranty claims for recently launched products that have short histories of claim records is vitally important for manufacturers in preparing their fiscal plans. Since the amount of historical claim data for such products is not large enough, developing forecasting models with good performance has been a difficult problem. The objective of this(More)
INTRODUCTION The extent of preventable medication-related hospital admissions and medication-related issues in primary care is significant enough to justify developing decision support systems for medication safety surveillance. The prerequisite for such systems is defining a relevant set of medication safety-related indicators and understanding the(More)
4 Sales delay is the time interval from the date of manufacture to the date of sale. In analysing 5 warranty claims data, the existing research relating to the sales delay has mainly focused 6 on estimating the probability distribution of the sales delay. Longer sales delay may lead 7 to more warranty claims as it can have an impact on the post-sale(More)
Nonadherence to antihypertensive treatment is a critical contributor to suboptimal blood pressure control. There are limited and heterogeneous data on the risk factors for nonadherence because few studies used objective-direct diagnostic methods. We used high-performance liquid chromatography-tandem mass spectrometry of urine and serum to detect(More)
STUDY QUESTION What is the prevalence of different types of potentially hazardous prescribing in general practice in the United Kingdom, and what is the variation between practices? METHODS A cross sectional study included all adult patients potentially at risk of a prescribing or monitoring error defined by a combination of diagnoses and prescriptions in(More)
INTRODUCTION Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of(More)
We demonstrate the use of electronic records and repeated measures of risk factors therein, to enable deeper understanding of the relationship between the full longitudinal trajectory of risk factors and outcomes. To illustrate, dynamic mixed effect modelling is used to summarise the level, trend and monitoring intensity of kidney function. The output from(More)
We compare the effectiveness of two types of verbal protocol, concurrent think aloud vs. retrospective sense making, for evaluating the usability of a clinical decision support tool. Thirty-five medical and nursing students participated in a usability experiment. Participants were asked to complete seven tasks using the system under evaluation. Eighteen(More)