Based on the free text data of virtual health community, this paper aims to construct a
detection model of adverse drug reaction events by using machine learning. Firstly, this …

El rápido crecimiento de las redes sociales se ha convertido en una fuente de información
útil para diferentes tareas debido a que los usuarios publican información valiosa sobre …

The aim of this work is the automatic extraction of Adverse Drug Reactions (ADRs) in
Electronic Health Records (EHRs) written in Spanish. From Natural Language Processing …

The rapid increase in the volume and variety of data poses a challenge to safe drug
prescription for the dentist. The increasing number of patients that take multiple drugs further …

This study presents a cellular automata (CA) model to assist decision-makers in
understanding the effects of infrastructure development projects on adverse events in an …

RESUMO A fusão de informações multissensor traz desafios como heterogeneidade de
dados, precisão de fonte e a fusão de incertezas que impactam a qualidade dos …

With the addition of new drugs in the market each year, the number of drugs in drug
databases is constantly expanding, posing a problem when prescribing medications for …

의학의 발전에 따라 환자는 다양한 처치와 처방을 받고 사용하는 약물이 증가하면서 약물로
인한 의도치 않은 해로운 반응인 약물유해반응 (Adverse Drug Reaction, ADR) 의 발생은 …

This paper discusses the application of text mining in medical field at home and abroad
based on overview and analysis of current literature data. Foreign researchers have specific …

The number of drugs in drug databases is constantly expanding with novel drugs appearing
on the market each year. A dentist cannot be expected to recall all the drugs available, let …