title: Automatically classifying sentences in full-text biomedical articles into introduction, methods, results and discussion.
abstract: BIOMEDICAL TEXTS CAN BE TYPICALLY REPRESENTED BY FOUR RHETORICAL CATEGORIES: introduction, methods, results and discussion (IMRAD). Classifying sentences into these categories can benefit many other text-mining tasks. Although many studies have applied approaches to automatically classify sentences in MEDLINE abstracts into the IMRAD categories, few have explored the classification of sentences that appear in full-text biomedical articles. We explored different approaches to automatically classify a sentence in a full-text biomedical article into the IMRAD categories. Our best system is a support vector machine classifier that achieved 81.30% accuracy, which is significantly higher than baseline systems.
authors.affiliation: Medical Informatics and.
authors.forename: Shashank
authors.initials: S
authors.lastname: Agarwal
authors.forename: Hong
authors.initials: H
authors.lastname: Yu