Summary: Objectives: Due to the narrow therapeutic range and high drug-to-drug interactions (DDIs), improving the adequate use of warfarin for the elderly is crucial in clinical practice. This study examines whether the effectiveness of using warfarin among elderly inpatients can be improved when machine learning techniques and data from the laboratory information system are incorporated.Methods: Having employed 288 validated clinical cases in the DDI group and 89 cases in the non-DDI group, we evaluate the prediction performance of seven classification techniques, with and without an Adaptive Boosting (AdaBoost) algorithm. Measures including accuracy, sensitivity, specificity and area under the curve are used to evaluate model performance.Results: Decision tree-based classifiers outperform other investigated classifiers in all evaluation measures. The classifiers supplemented with AdaBoost can generally improve the performance. In addition, weight, congestive heart failure, and gender are among the top three critical variables affecting prediction accuracy for the non-DDI group, while age, ALT, and warfarin doses are the most influential factors for the DDI group.Conclusion: Medical decision support systems incorporating decision tree-based approaches improve predicting performance and thus may serve as a supplementary tool in clinical practice. Information from laboratory tests and inpatients’ history should not be ignored because related variables are shown to be decisive in our prediction models, especially when the DDIs exist.

A return visit (RV) to the emergency department (ED) is usually used as a quality indicator for EDs. A thorough comprehension of factors affecting RVs is beneficial to enhancing the quality of emergency care. We performed this study to identify pediatric patients at high risk of RVs using readily available characteristics during an ED visit. We retrospectively collected data of pediatric patients visiting 6 branches of an urban hospital during 2007. Potential variables were analyzed using a multivariable logistic regression analysis to determine factors associated with RVs and a classification and regression tree technique to identify high-risk groups. Of the 35,435 visits from which patients were discharged home, 2291 (6.47%) visits incurred an RV within 72 hours. On multivariable analysis, younger age, weekday visits, diagnoses belonging to the category of symptoms, signs, and ill-defined conditions, and being seen by a female physician were associated with a higher probability of RVs. Children younger than 6.5 years who visited on weekdays or between midnight and 8:00 AM on weekends or holidays had the highest probability of returning to the ED within 72 hours. Our study reexamined several important factors that could affect RVs of pediatric patients to the ED and identified high-risk groups of RVs. Further intervention studies or qualitative research could be targeted on these at-risk groups.

This paper investigates the expenditure allocation of Japanese international tourism in its five major Asian destinations, China, Hong Kong, Korea, Taiwan, and Thailand. The dynamic of linear approximation the almost ideal demand system is used to determine the long-run equilibrium while the short-run dynamics are represented by an error correction mechanism. The empirical results indicate that the changes in market shares of Japanese outbound tourism are significantly influenced by the changes in tourists' expenditure, rather than the changes in relative tourism prices. The results show that Japan expenditure rises, the market share of Taiwan and Thailand declines, while Korea benefits. In addition, price competitiveness is important for Japanese demand for Korea, but is relatively unimportant for the other destinations.

Most consumers in Taiwan have never eaten pure rice noodles (PRNs) and some may mistakenly treat corn starch-based rice noodles as PRNs. This study examines consumers’ willingness to pay (WTP) for PRNs using discrete choice (DC) experiments with a blind tasting test to understand consumers’ ability to identify PRNs with varying rice content on the basis of their appearance and taste. Collecting data from the Taipei metropolitan area, our DC experimental results of both pre- and post-experiment conditions show that Taiwanese consumers do prefer PRNs and their WTP for PRNs was strengthened. A latent class model highlights that attribute preferences tend to differ by group and thus rice content ratios should be properly labeled so that consumers can make a better choice according to their preferences. Our WTP estimates also imply that offering tasting trials to consumers is an effective marketing strategy to encourage potential purchases of PRNs for the rice noodle industry.

This study examined consumer risk perceptions and knowledge of avian influenza and its linkage to behavioral changes in chicken consumption. A consum

Purpose – The purpose of this paper is to fill a knowledge gap by examining the changes in fruit and vegetable consumption of Chinese households. Design/methodology/approach – Using 1993 and 2001 household survey data from three selected provinces in China, the authors estimated a quantile regression (QR) model to demonstrate how changes of fresh fruit and vegetable consumption over time may differ across regions, and additionally, how these changes may differ over the entire distribution. Findings – Results show significant increases in fresh fruit consumption for all provinces; in addition, the pattern of changes over time differs across the entire distribution. In contrast, significant decreases of fresh vegetable consumption are evident, and results are robust across regions; however, the disparities of fresh vegetable consumption across regions are not significant. Research limitations/implications – The results may shed some light on the national food policy. First, any food policy that may affect prices of fresh fruits and vegetables will likely affect households in lower percentiles more than those in upper percentiles. In addition, based on the findings, households in Guangdong may have a higher risk of inadequate fruit consumption. Lower level consumption of fruits in Guangdong may be caused by its relatively high prices of fruits and perhaps the shifting consumption pattern to a more meat-based diet as income increases. Originality/value – There has been considerable interest in estimating food demand structure in China due to its huge market for food products. However, little is known about the fruits and vegetables products. In addition, most of the previous studies used the linear regression-type model for analysis, which fails to capture the effects of the exogenous factors on the entire distribution. To fill the knowledge gap, this paper uses a QR model with the different-in-difference method to examine the changes in fruit and vegetable consumption of Chinese households.