Induced lexico-syntactic patterns improve information extraction from online medical forums.

ABSTRACT:

Objective

To reliably extract two entity types, symptoms and conditions (SCs), and drugs and treatments (DTs), from patient-authored text (PAT) by learning lexico-syntactic patterns from data annotated with seed dictionaries.

Background and significance

Despite the increasing quantity of PAT (eg, online discussion threads), tools for identifying medical entities in PAT are limited. When applied to PAT, existing tools either fail to identify specific entity types or perform poorly. Identification of SC and DT terms in PAT would enable exploration of efficacy and side effects for not only pharmaceutical drugs, but also for home remedies and components of daily care.

Materials and methods

We use SC and DT term dictionaries compiled from online sources to label several di

SUBMITTER: Gupta S 

PROVIDER: S-EPMC4147618 | biostudies-literature | 2014 Sep-Oct

REPOSITORIES: biostudies-literature