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Minimalistic Approach to Coreference Resolution in Lithuanian Medical Records
Voldemaras Žitkus1, Rita Butkienė1, Rimantas Butleris1
1Faculty of Informatics, Kaunas University of Technology, 51386 Kaunas, Lithuania.
Computational and Mathematical Methods in Medicine
|April 25, 2019
Summary
We developed a novel method for coreference resolution in Lithuanian, a low-resource language. This natural language processing technique enables efficient e-health record analysis for improved healthcare services.
Area of Science:
- Natural Language Processing
- Computational Linguistics
- Health Informatics
Background:
- Coreference resolution is crucial for information extraction in Natural Language Processing (NLP).
- Resource-scarce languages, like Lithuanian, face significant challenges due to a lack of linguistic tools.
- Existing NLP methods often require extensive language resources, limiting their applicability.
Purpose of the Study:
- To present a novel method for coreference resolution specifically for the Lithuanian language.
- To demonstrate the application of this method in processing electronic health records (e-health).
- To address the challenge of limited linguistic resources for NLP in under-resourced languages.
Main Methods:
- Developed a coreference resolution technique requiring minimal linguistic resources.
- Applied the method to analyze Lithuanian e-health records from a hospital setting.
- Focused on adaptability for rare and endangered languages.
Main Results:
- Successfully implemented coreference resolution for Lithuanian.
- Demonstrated the method's effectiveness in processing e-health data.
- Validated the approach's viability for low-resource language NLP applications.
Conclusions:
- Coreference resolution is feasible for Lithuanian with minimal resources.
- The developed NLP method can support the creation of online healthcare services in Lithuania.
- This work contributes to advancing NLP for under-resourced languages in specialized domains.
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