title: Expertizer: a tool to assess the expert level of online health websites.
abstract: Health-related Web sites have become a primary resource to search for information on diseases, diagnoses or treatment options. Various Web sites offer a great variety of such information. However, lay people might have difficulties to assess whether a certain article or Web site fits their individual level of understandability. Hence, they might get overwhelmed with the delivered complexity of medical information. In this paper, we present a Web browser plugin, Expertizer that supports users in order to easily assess the expert level of textual medical Web content. The plugin communicates with a Web service, which leverages pre-computed classification models based on a Support Vector Machine.
authors.affiliation: Dept. of Medical Informatics, Heilbronn University, Heilbronn, Germany.
authors.forename: Richard
authors.initials: R
authors.lastname: Zowalla
authors.affiliation: Dept. of Medical Informatics, Heilbronn University, Heilbronn, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Wiesner
authors.affiliation: Dept. of Medical Informatics, Heilbronn University, Heilbronn, Germany.
authors.forename: Daniel
authors.initials: D
authors.lastname: Pfeifer
mesh_terms: D002983:Clinical Competence; D054626:Consumer Health Information / Q000145:classification*; D005103:Expert Systems; D009323:Natural Language Processing; D009862:Online Systems; D061108:Social Media / Q000145:classification*; D060388:Support Vector Machine; D064878:Web Browser