Automated learning of everyday patients' language for medical blogs analytics

Giovanni Stilo; Moreno De Vincenzi; Alberto E. Tozzi; Paola Velardi

Automated learning of everyday patients' language for medical blogs analytics

Giovanni Stilo, Moreno De Vincenzi, Alberto E. Tozzi, Paola Velardi

Ospedale Pediatrico Bambino Gesu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	International Conference Recent Advances in Natural Language Processing, RANLP
Pages	640-648
Number of pages	9
Publication status	Published - 2013
Event	9th International Conference on Recent Advances in Natural Language Processing, RANLP 2013 - Hissar, Bulgaria Duration: Sep 9 2013 → Sep 11 2013

Other

Other	9th International Conference on Recent Advances in Natural Language Processing, RANLP 2013
Country	Bulgaria
City	Hissar
Period	9/9/13 → 9/11/13

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Software
Electrical and Electronic Engineering

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title = "Automated learning of everyday patients' language for medical blogs analytics",

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.",

author = "Giovanni Stilo and {De Vincenzi}, Moreno and Tozzi, {Alberto E.} and Paola Velardi",

year = "2013",

language = "English",

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booktitle = "International Conference Recent Advances in Natural Language Processing, RANLP",

note = "9th International Conference on Recent Advances in Natural Language Processing, RANLP 2013 ; Conference date: 09-09-2013 Through 11-09-2013",

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AU - De Vincenzi, Moreno

AU - Tozzi, Alberto E.

AU - Velardi, Paola

PY - 2013

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N2 - 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.

AB - 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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AN - SCOPUS:84890543001

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EP - 648

BT - International Conference Recent Advances in Natural Language Processing, RANLP

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Y2 - 9 September 2013 through 11 September 2013

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