Radiology departments utilize various visualization techniques of patients&rsquo / bodies, and narrative free text reports describing the findings in these visualizations are written by medical doctors. The information within these narrative reports is required to be extracted for medical information systems. Turkish is an highly agglutinative language and this poses problems in information retrieval and extraction from Turkish free texts.
In this thesis one rule-based and one data-driven alternate methods for information retrieval and structured information extraction from Turkish radiology reports are presented. Contrary to previous studies in medical NLP systems, both of these methods do not utilize any medical lexicon or ontology.
Information extraction is performed on the level of extracting medically related phrases from the sentence. The aim is to measure baseline performance Turkish language can provide for medical information extraction and retrieval, in isolation of other factors.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12613280/index.pdf |
| Date | 01 May 2011 |
| Creators | Hadimli, Kerem |
| Contributors | Ucoluk, Gokturk |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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