Extracting health-related causality from twitter messages using natural language processing.

Background: Twitter messages (tweets) contain various types of topics in our daily life, which include health-related topics. Analysis of health-related tweets would help us understand health conditions and concerns encountered in our daily lives. In this paper we evaluate an approach to extracting causalities from tweets using natural language processing (NLP) techniques.

A Preliminary Study of Clinical Concept Detection Using Syntactic Relations.

Concept detection is an integral step in natural language processing (NLP) applications in the clinical domain. Clinical concepts are detailed (e.g.

Syntactic parsing of clinical text: guideline and corpus development with handling ill-formed sentences.

Objective: To develop, evaluate, and share: (1) syntactic parsing guidelines for clinical text, with a new approach to handling ill-formed sentences; and (2) a clinical Treebank annotated according to the guidelines. To document the process and findings for readers with similar interest.

Methods: Using random samples from a shared natural language processing challenge dataset, we developed a handbook of domain-customized syntactic parsing guidelines based on iterative annotation and adjudication between two institutions.