BACKGROUND Medical students are usually under more stress than that experienced by non-medical students. Stress testing tools for Korean medical students have not been sufficiently studied. Thus, we adapted and modified the East Asian Student Stress Inventory (EASSI), a stress testing tool for Korean students studying abroad, and verified its usefulness as a stress test in Korean university stu...

user-generated medical messages on internet contain extensive information related to adverse drug reactions (adrs) and are known as valuable resources for post-marketing drug surveillance. the aim of this study was to find an effective method to identify messages related to adrs automatically from online user reviews.we conducted experiments on online user reviews using different feature set an...

Woodland detection in an urban environment was conducted using Ikonos multispectral images over the city of Sherbrooke (Quebec, Canada). The detection process is composed of two parts. The first is a combination-based classification that uses radiometric and color-texture information. The color-texture feature is derived by integrative scheme using the wavelet transform. The second part is an o...

Assessing the accuracy of land cover maps is often prohibitively expensive because of the difficulty of collecting a statistically valid probability sample from the classified map. Even when post-classification sampling is undertaken, cost and accessibility constraints may result in imprecise estimates of map accuracy. If the map is constructed via supervised classification, then the training s...

Introduction: To develop different radiomic models based on radiomic features and machine learning methods to predict early intensity modulated radiation therapy (IMRT) response.   Materials and Methods: Thirty prostate patients were included. All patients underwent pre ad post-IMRT T2 weighted and apparent diffusing coefficient (ADC) magnetic resonance imagi...

Lack of detailed land use (LU) information and efficient data collection methods have made the modeling of urban systems difficult. This study aims to develop a novel hierarchical rule-based LU extraction framework using geographic vector and remotely sensed (RS) data, in order to extract detailed subzonal LU information, residential LU in this study. The LU extraction system is developed to ex...

Abstract Post-hoc interpretability methods are critical tools to explain neural-network results. Several post-hoc have emerged in recent years but they produce different results when applied a given task, raising the question of which method is most suitable provide accurate interpretability. To understand performance each method, quantitative evaluation essential; however, currently available ...

In this paper we study a new technique we call post-bagging, which consists in resampling parts of a classification model rather then the data. We do this with a particular kind of model: large sets of classification association rules, and in combination with ordinary best rule and weighted voting approaches. We empirically evaluate the effects of the technique in terms of classification accura...