Annotation for Information Extraction from Mammography Reports

Bozkurt S., GÜLKESEN K. H., Rubin D.

11th International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH), Athens, Yunanistan, 5 - 07 Temmuz 2013, cilt.190, ss.183-185 identifier identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 190
  • Doi Numarası: 10.3233/978-1-61499-276-9-183
  • Basıldığı Şehir: Athens
  • Basıldığı Ülke: Yunanistan
  • Sayfa Sayıları: ss.183-185
  • Anahtar Kelimeler: mammography, decision support systems, natural language processing, VARIABILITY
  • Akdeniz Üniversitesi Adresli: Evet

Özet

Inter and intra-observer variability in mammographic interpretation is a challenging problem, and decision support systems (DSS) may be helpful to reduce variation in practice. Since radiology reports are created as unstructured text reports, Natural language processing (NLP) techniques are needed to extract structured information from reports in order to provide the inputs to DSS. Before creating NLP systems, producing high quality annotated data set is essential. The goal of this project is to develop an annotation schema to guide the information extraction tasks needed from free-text mammography reports.