OBJECTIVE The goal of this work was to evaluate machine learning methods, binary classification and sequence labeling, for medication-attribute linkage detection in two clinical corpora. DATA AND METHODS We double annotated 3000 clinical trial announcements (CTA) and 1655 clinical notes (CN) for medication named entities and their attributes. A binary support vector machine (SVM) classificati...

introduction: soil aggregate stability is a key factor in soil resistivity to mechanical stresses, including the impacts of rainfall and surface runoff, and thus to water erosion (canasveras et al., 2010). various indicators have been proposed to characterize and quantify soil aggregate stability, for example percentage of water-stable aggregates (wsa), mean weight diameter (mwd), geometric mea...

Recently, the use of Receiver Operating Characteristic (ROC) Curve and the area under the ROC Curve (AUC) has been receiving much attention as a measure of the performance of machine learning algorithms. In this paper, we propose a SVM classifier fusion model using genetic fuzzy system. Genetic algorithms are applied to tune the optimal fuzzy membership functions. The performance of SVM classif...

background: water is considered as the main source of life but water resources are limited and nonrenewable. different factors have caused groundwater to decrease. therefore, modeling and predicting groundwater level is of great importance. methods: monthly groundwater level data of about 20 years (october 1991 to february 2012) from the hamadan-bahar plain, west of iran were used based on peiz...

M e t h o d s Design: Randomized controlled trial (Standard and New Antiepileptic Drugs [SANAD] trial, Arm B). Allocation: Concealed.* Blinding: Unblinded.* Follow-up period: Up to 6 years. Setting: Hospital-based outpatient clinics in the United Kingdom. Patients: 716 patients (mean age 23 y, 60% men) who had ≥ 2 clinically definite, unprovoked epileptic seizures in the past year and were reco...