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Towards the semantic interpretation of personal health messages from social media


Type

Conference Object

Change log

Authors

Limsopatham, N 

Abstract

Recent attempts have been made to utilise social media platforms, such as Twitter, to provide early warning and monitoring of health threats in populations (i.e. Internet biosurveillance). It has been shown in the literature that a system based on keyword matching that exploits social media messages could report flu surveillance well ahead of the Centers of Disease Control and Prevention (CDC). However, we argue that a simple keyword matching may not capture semantic interpretation of social media messages that would enable healthcare experts or machines to extract and leverage medical knowledge from social media messages. In this paper, we motivate and describe a new task that aims to tackle this technology gap by extracting semantic interpretation of medical terms mentioned in social media messages, which are typically written in layman’s language. Achieving such a task would enable an automatic integration between the data about direct patient experiences extracted from social media and existing knowledge from clinical databases, which leads to advances in the use of community health experiences in healthcare services.

Description

Keywords

Medical Concept Coding, Internet Biosurveillance

Journal Title

UCUI 2015 - Proceedings of the ACM 1st International Workshop on Understanding the City with Urban Informatics, co-located with CIKM 2015

Conference Name

CIKM'15: 24th ACM International Conference on Information and Knowledge Management

Journal ISSN

Volume Title

Publisher

ACM
Sponsorship
Engineering and Physical Sciences Research Council (EP/M005089/1)
The authors gratefully acknowledge funding from the EPSRC (grant number EP/M005089/1)