A study of drug interaction for personalised decision support in dental clinics
Paper
Paper/Presentation Title | A study of drug interaction for personalised decision support in dental clinics |
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Presentation Type | Paper |
Authors | Goh, Wee Pheng (Author), Tao, Xiaohui (Author), Zhang, Ji (Author) and Yong, Jianming (Author) |
Journal or Proceedings Title | Proceedings of the 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2015) |
ERA Conference ID | 60342 |
Journal Citation | 1, pp. 88-91 |
Number of Pages | 4 |
Year | 2015 |
ISBN | 9781467396189 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/WI-IAT.2015.28 |
Web Address (URL) of Paper | http://dblp.uni-trier.de/db/conf/iat/ |
Conference/Event | 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2015) |
IEEE/WIC/ACM International Conference on Web Intelligence (WI) | |
Event Details | 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2015) Event Date 06 to end of 09 Dec 2015 Event Location Singapore |
Event Details | IEEE/WIC/ACM International Conference on Web Intelligence (WI) WI |
Abstract | While most dental clinicians use some sort of information system, they are mainly for administrative purposes, with a noticeable lack in advisory features such as decision support in clinical situations. It will be exciting to see more research done to enable a robust system that can fit within the clinical workflow of the dentist to be used as a diagnostic tool at point-of-care, especially in drug prescription. With this motivation in mind, this paper proposes a model to store interactive drug-pairs and other useful information such as side-effects of the drugs. By traversing through these drug- pairs, potential interactions can be highlighted to the dentist by considering the personalised medical and drug profiles of the patient. This will enhance the potential for seamless integration of a robust, intelligent and scalable diagnostic tool within the clinical workflow of a dental clinic, thereby reducing prescription errors and increasing productivity of the dental practice |
Keywords | clinical decision support; decision-making; dentistry; personalised drug detection |
ANZSRC Field of Research 2020 | 460902. Decision support and group support systems |
469999. Other information and computing sciences not elsewhere classified | |
Public Notes | © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Byline Affiliations | School of Agricultural, Computational and Environmental Sciences |
School of Management and Enterprise | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q3452/a-study-of-drug-interaction-for-personalised-decision-support-in-dental-clinics
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