Keyword Extraction and Structuralization for Medical Report
| Autor: | Wu, Pei-Hao, 吳培豪 |
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| Rok vydání: | 2017 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 105 In recent years, the patients usually accept more and more accurate and detailed examinations because of the rapid advances in medical technology. Many of the examination reports are not represented in numerical data, but are text documents written by the medical examiners according to the observations obtained from the instruments and biochemical tests. If the above-mentioned unstructured data can be converted into a examination report in a structured form, it will help the doctors to understand the patient's status in different examination items more efficiently. Besides, further association analysis on the structural data can be performed to identify potential factors that affect a disease. In this thesis, from the pathology examination reports of renal disease, we applied the POS tagging result of natural language analysis to automatically extract the keyword phrases. Then a medical vocabulary dictionary of examination report for each paragraph is established, which is used as the basic information for retrieving the terms to construct a structured form of the report. Besides, a topic probability modeling method is applied to automatically find the keywords of the examination items from the reports. Finally, a system is implemented to generate the structured form for the various types of paragraphs in an examination report with the assistance of the constructed medical dictionary. The results of experiments showed that the methods proposed in this paper can effectively construct a structural form of examination reports. Furthermore, the keywords of the popular examination items can be extracted correctly. The above techniques will help automatic processing and analysis of medical text reports. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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