An enhanced CRFs-based system for information extraction from radiology reports (Articolo in rivista)

Type

• Articolo in rivista (Classe)
• Prodotto della ricerca (Classe)

Label

• An enhanced CRFs-based system for information extraction from radiology reports (Articolo in rivista) (literal)

Anno

• 2013-01-01T00:00:00+01:00 (literal)

Alternative label

• Esuli A., Marcheggiani D., Sebastiani F. (2013)
  An enhanced CRFs-based system for information extraction from radiology reports
  in Journal of biomedical informatics
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Esuli A., Marcheggiani D., Sebastiani F. (literal)

Pagina inizio

• 425 (literal)

Pagina fine

• 435 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni

• ISSN 1532-0464 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url

• http://www.sciencedirect.com/science/article/pii/S1532046413000191 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 46 (literal)

Rivista

• Journal of biomedical informatics (Rivista)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo

• 3 (literal)

Note

• ISI Web of Science (WOS) (literal)
• Scopu (literal)
• PuMa (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy (literal)

Titolo

• An enhanced CRFs-based system for information extraction from radiology reports (literal)

Abstract

• We discuss the problem of performing information extraction from free-text radiology reports via supervised learning. In this task, segments of text (not necessarily coinciding with entire sentences, and possibly crossing sentence boundaries) need to be annotated with tags representing concepts of interest in the radiological domain. In this paper we present two novel approaches to IE for radiology reports: (i) a cascaded, two-stage method based on pipelining two taggers generated via the well known linear-chain conditional random fields (LC-CRFs) learner and (ii) a confidence-weighted ensemble method that combines standard LC-CRFs and the proposed two-stage method. We also report on the use of \"positional features\", a novel type of feature intended to aid in the automatic annotation of texts in which the instances of a given concept may be hypothesized to systematically occur in specific areas of the text. We present experiments on a dataset of mammography reports in which the proposed ensemble is shown to outperform a traditional, single-stage CRFs system in two different, applicatively interesting scenarios. (literal)

Prodotto di

• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Digital Libraries (ICT.P08.010.002) (Modulo)

Autore CNR

• Diego Marcheggiani (Unità di personale esterno)
• FABRIZIO SEBASTIANI (Unità di personale interno)
• ANDREA ESULI (Unità di personale interno)

Insieme di parole chiave

• Keywords of "An enhanced CRFs-based system for information extraction from radiology reports" (Insieme di parole chiave)

Incoming links:

Prodotto

• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Digital Libraries (ICT.P08.010.002) (Modulo)

Autore CNR di

• FABRIZIO SEBASTIANI (Unità di personale interno)
• Diego Marcheggiani (Unità di personale esterno)
• ANDREA ESULI (Unità di personale interno)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• Journal of biomedical informatics (Rivista)

Insieme di parole chiave di

• Keywords of "An enhanced CRFs-based system for information extraction from radiology reports" (Insieme di parole chiave)