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; Alberto E., Tozzi; Velardi, Paola; DE VINCENZI, Moreno. - 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
