title: Improving Search for Evidence-based Practice using Information Extraction.
abstract: The search for applicable and valid research evidence-based practice articles is not supported well in common EBP resources, as some crucial study data, such as patient details, study design and results, are not available or presented explicitly. We propose to extract these data from research articles using a two-step supervised soft classification method. Compared to manual annotation, our approach is less labor-intensive and more flexible, hence opening up the possibility of utilizing these data to facilitate the evidence selection process in information seeking support systems.
authors.affiliation: National University of Singapore, Singapore.
authors.forename: Jin
authors.initials: J
authors.lastname: Zhao
authors.forename: Min-Yen
authors.initials: MY
authors.lastname: Kan
authors.forename: Paula M
authors.initials: PM
authors.lastname: Procter
authors.forename: Siti
authors.initials: S
authors.lastname: Zubaidah
authors.forename: Wai Kin
authors.initials: WK
authors.lastname: Yip
authors.forename: Goh Mien
authors.initials: GM
authors.lastname: Li
mesh_terms: D055317:Evidence-Based Practice; D006801:Humans; D016247:Information Storage and Retrieval