Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/72664
DC Field | Value | |
---|---|---|
dc.title | Graphical knowledge-based protocols for chest pain management | |
dc.contributor.author | Ali, S. | |
dc.contributor.author | Chia, P. | |
dc.contributor.author | Ong, K. | |
dc.date.accessioned | 2014-06-19T05:10:37Z | |
dc.date.available | 2014-06-19T05:10:37Z | |
dc.date.issued | 1999 | |
dc.identifier.citation | Ali, S.,Chia, P.,Ong, K. (1999). Graphical knowledge-based protocols for chest pain management. Computers in Cardiology : 309-312. ScholarBank@NUS Repository. | |
dc.identifier.issn | 02766574 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/72664 | |
dc.description.abstract | We present an automated delivery system for clinical guidelines (DSCG) that assists clinicians in diagnosing and treating patients with chest pain in the emergency department. Guidelines are adaptively selected from a knowledge base server that has a library of clinically defined, graphical guidelines. As one of the components of a hospital information system architecture that we are developing, the DSCG system is positioned to improve diagnostic efficiency. The system receives patient data, such as complaints and test results, and matches these data with eligibility criteria. It recommends optimal treatment plans and investigations based on the most probable diagnosis. Clinicians may either use the suggestions as a reference or activate a selection to monitor the patient's condition during the treatment using an intelligent agent. The system is also being considered for use in medical education. | |
dc.source | Scopus | |
dc.type | Conference Paper | |
dc.contributor.department | ELECTRICAL ENGINEERING | |
dc.description.sourcetitle | Computers in Cardiology | |
dc.description.page | 309-312 | |
dc.description.coden | COCAD | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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