Entity recognition in the biomedical domain using a hybrid approach.

Background: This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles.

Method: The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies.

Web Conversations About Complementary and Alternative Medicines and Cancer: Content and Sentiment Analysis.

Background: The use of complementary and alternative medicine (CAM) among cancer patients is widespread and mostly self-administrated. Today, one of the most relevant topics is the nondisclosure of CAM use to doctors. This general lack of communication exposes patients to dangerous behaviors and to less reliable information channels, such as the Web.