IR @ Nirma University
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http://10.1.7.192:80/jspui/handle/123456789/5876| Title: | Modifier Detection and Classification in Clinical Text |
| Authors: | Dani, Kinjal T. |
| Keywords: | Computer 2013 Project Report 2013 Computer Project Report Project Report 13MCEI 13MCEI29 INS INS 2013 CE (INS) |
| Issue Date: | 1-Jun-2015 |
| Publisher: | Institute of Technology |
| Series/Report no.: | 13MCEI29; |
| Abstract: | In USA Health Care, whenever a patient visits to a hospital or clinic, all the infor- mation regarding that visit is documented. This formal document is known as Clinical Document. A clinical document contains vital information about patient's health in un- structured free text format, so Information Extraction and Clinical Entity Recognition are essential to extract meaningful information from this free clinical text. In this project we have tried to detect different modifiers related to clinical Entity and classify it into different categories.We have used Crf algorithm for classification and have obtained av- erage accuracy of 00% .And also tried to Find the boundary of this modifier using Crf algorithm,Binary SVM and rules based approached and obtained the accuracy of: 00 %,00% and 00% respectively |
| URI: | http://hdl.handle.net/123456789/5876 |
| Appears in Collections: | Dissertation, CE (INS) |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 13MCEI29.pdf | 13MCEI29 | 776.89 kB | Adobe PDF |  View/Open |
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