Drug prescription support in dental clinics through drug corpus mining

Goh, Wee Pheng and Tao, Xiaohui and Zhang, Ji and Yong, Jianming and Zhang, Wenping and Xie, Haoran (2018) Drug prescription support in dental clinics through drug corpus mining. International Journal of Data Science and Analytics, 6 (4). pp. 341-349. ISSN 2364-415X

Abstract

The rapid increase in the volume and variety of data poses a challenge to safe drug prescription for the dentist. The increasing number of patients that take multiple drugs further exerts pressure on the dentist to make the right decision at point-of-care. Hence, a robust decision support system will enable dentists to make decisions on drug prescription quickly and accurately. Based on the assumption that similar drug pairs have a higher similarity ratio, this paper suggests an innovative approach to obtain the similarity ratio between the drug that the dentist is going to prescribe and the drug that the patient is currently taking. We conducted experiments to obtain the similarity ratios of both positive and negative drug pairs, by using feature vectors generated from term similarities and word embeddings of biomedical text corpus. This model can be easily adapted and implemented for use in a dental clinic to assist the dentist in deciding if a drug is suitable for prescription, taking into consideration the medical profile of the patients. Experimental evaluation of our model’s association of the similarity ratio between two drugs yielded a superior F score of 89%. Hence, such an approach, when integrated within the clinical work flow, will reduce prescription errors and thereby increase the health outcomes of patients.


Statistics for USQ ePrint 34863
Statistics for this ePrint Item
Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Copy of publication not accessible until Jan 2020.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences
Date Deposited: 01 Feb 2019 05:33
Last Modified: 05 Feb 2019 01:44
Uncontrolled Keywords: Adverse relationship; Word embeddings; Term similarity; Personalised prescription; Drug properties
Fields of Research : 08 Information and Computing Sciences > 0806 Information Systems > 080605 Decision Support and Group Support Systems
Identification Number or DOI: 10.1007/s41060-018-0149-3
URI: http://eprints.usq.edu.au/id/eprint/34863

Actions (login required)

View Item Archive Repository Staff Only