Please use this identifier to cite or link to this item:
http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/3852Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Li, Xiaoli | - |
| dc.creator | Leong, Tze Yun | - |
| dc.date | 2003-12-13T18:57:27Z | - |
| dc.date | 2003-12-13T18:57:27Z | - |
| dc.date | 2004-01 | - |
| dc.date.accessioned | 2013-10-09T02:32:49Z | - |
| dc.date.available | 2013-10-09T02:32:49Z | - |
| dc.date.issued | 2013-10-09 | - |
| dc.identifier | http://hdl.handle.net/1721.1/3852 | - |
| dc.identifier.uri | http://koha.mediu.edu.my:8181/xmlui/handle/1721 | - |
| dc.description | We propose an information extraction framework to support automated construction of decision models in biomedicine. Our proposed technique classifies text-based documents from a large biomedical literature repository, e.g., MEDLINE, into predefined categories, and identifies important keywords for each category based on their discriminative power. Relevant documents for each category are retrieved based on the keywords, and a classification algorithm is developed based on machine learning techniques to build the final classifier. We apply the HITS algorithm to select the authoritative and typical documents within a category, and construct templates in the form of Bayesian networks. Data mining and information extraction techniques are then applied to extract the necessary semantic knowledge to fill in the templates to construct the final decision models. | - |
| dc.description | Singapore-MIT Alliance (SMA) | - |
| dc.format | 125335 bytes | - |
| dc.format | application/pdf | - |
| dc.language | en_US | - |
| dc.relation | Computer Science (CS); | - |
| dc.subject | data mining | - |
| dc.subject | decision model | - |
| dc.subject | information extraction | - |
| dc.title | Automated Information Extraction to Support Biomedical Decision Model Construction: A Preliminary Design | - |
| dc.type | Article | - |
| Appears in Collections: | MIT Items | |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.