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.

Automated learning of everyday patients' language for medical blogs analytics / Stilo, Giovanni; Moreno De, Vincenzi; Alberto E., Tozzi; Velardi, Paola. - STAMPA. - (2013), pp. 640-648. ((Intervento presentato al convegno Recent Advances in Natural Language Processing tenutosi a Hissar, Bulgaria nel 9-11 September, 2013.

Automated learning of everyday patients' language for medical blogs analytics

STILO, GIOVANNI;VELARDI, Paola;DE VINCENZI, MORENO
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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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11573/781953
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