Login / Signup

Minimalistic Approach to Coreference Resolution in Lithuanian Medical Records.

Voldemaras ŽitkusRita ButkienėRimantas ButlerisRytis MaskeliunasRobertas DamaseviciusMarcin Woźniak
Published in: Computational and mathematical methods in medicine (2019)
Coreference resolution is a challenging part of natural language processing (NLP) with applications in machine translation, semantic search and other information retrieval, and decision support systems. Coreference resolution requires linguistic preprocessing and rich language resources for automatically identifying and resolving such expressions. Many rarer and under-resourced languages (such as Lithuanian) lack the required language resources and tools. We present a method for coreference resolution in Lithuanian language and its application for processing e-health records from a hospital reception. Our novelty is the ability to process coreferences with minimal linguistic resources, which is important in linguistic applications for rare and endangered languages. The experimental results show that coreference resolution is applicable to the development of NLP-powered online healthcare services in Lithuania.
Keyphrases
  • healthcare
  • single molecule
  • autism spectrum disorder
  • health information
  • mental health
  • public health
  • primary care
  • risk assessment
  • machine learning
  • social media
  • deep learning
  • health promotion