Analyzing how people discuss about health-related topics on dedicated forums and social networks such as Twitter, can provide valuable insight for syndromic surveillance and to predict disease outbreaks. In this paper we present a minimally trained algorithm to learn associations between technical and everyday language terms, based on pattern generalization and complete linkage clustering, and we then assess its utility on a case study of five common syndromes for surveillance purposes.
Stilo, Giovanni; Moreno De, Vincenzi; Alberto E., Tozzi; Velardi, Paola. (2013). Automated learning of everyday patients' language for medical blogs analytics. In Proceedings of the International Conference Recent Advances in Natural Language Processing RANLP 2013 (pp. 640- 648). http://aclweb.org/anthology/R13-1084.
Automated learning of everyday patients' language for medical blogs analytics
STILO, GIOVANNIMembro del Collaboration Group
;
2013
Abstract
Analyzing how people discuss about health-related topics on dedicated forums and social networks such as Twitter, can provide valuable insight for syndromic surveillance and to predict disease outbreaks. In this paper we present a minimally trained algorithm to learn associations between technical and everyday language terms, based on pattern generalization and complete linkage clustering, and we then assess its utility on a case study of five common syndromes for surveillance purposes.
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