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Automatically Assessing the Expert Degree of Online Health Content using SVMs
Richard Zowalla, Martin Wiesner, Daniel Pfeifer
48 - 51
10.3233/978-1-61499-423-7-48
Studies in Health Technology and Informatics
Volume 202: Integrating Information Technology and Management for Quality of Care
Abstract

More and more people search for health information regarding diseases, diagnoses and treatments over the Web. However, lay people often have difficulties in assessing the understandability of related articles. Therefore, they could benefit from a system, which computes the medical expert degree of a corresponding piece of text in advance. In this paper we present an approach to automatically compute this expert degree using a machine learning approach. For evaluation purposes we constructed a large text corpus and tested our trained text classifier, which is based on Support Vector Machines.

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