Association rule mining for the ordered placement of traditional Chinese medicine containers: An experimental study. Issue 18 (May 2020)
- Record Type:
- Journal Article
- Title:
- Association rule mining for the ordered placement of traditional Chinese medicine containers: An experimental study. Issue 18 (May 2020)
- Main Title:
- Association rule mining for the ordered placement of traditional Chinese medicine containers
- Authors:
- Chen, Chih-Wen
Tsai, Chih-Fong
Tsai, Yi-Hong
Wu, Yang-Chang
Chang, Fang-Rong - Other Names:
- Aslam. Muhammad Shahzad section editor.
- Abstract:
- Abstract : Abstract: In traditional Chinese medicine (TCM) clinics, the pharmacists responsible for dispensing the herbal medicine usually find the desired ingredients based on positions of the shelves (racks; frames; stands). Generally, these containers are arranged in an alphabetical order depending on the herbal medicine they contain. However, certain related ingredients tend to be used together in many prescriptions, even though the containers may be stored far away from each other. This can cause problems, especially when there are many patients and/or the limited number of pharmacists. If the dispensing time takes longer, it is likely to impact the satisfaction of the patients' experience. Moreover, the stamina of the pharmacists will be consumed quickly. In this study, we investigate on an association rule mining technology to improve efficiency in TCM dispensing based on the frequent pattern growth algorithm and try to identify which 2 or 3 herbal medicines will match together frequently in prescriptions. Furthermore, 3 experimental studies are conducted based on a dataset collected from a traditional Chinese medicine hospital. The dataset includes information for an entire year (2014), including 4 seasons and doctors. Afterward, a questionnaire on the usefulness of the extracted rules was administered to the pharmacists in the case hospital. The responses showed the mining results to be very valuable as a reference for the placement and ordering of the frames in theAbstract : Abstract: In traditional Chinese medicine (TCM) clinics, the pharmacists responsible for dispensing the herbal medicine usually find the desired ingredients based on positions of the shelves (racks; frames; stands). Generally, these containers are arranged in an alphabetical order depending on the herbal medicine they contain. However, certain related ingredients tend to be used together in many prescriptions, even though the containers may be stored far away from each other. This can cause problems, especially when there are many patients and/or the limited number of pharmacists. If the dispensing time takes longer, it is likely to impact the satisfaction of the patients' experience. Moreover, the stamina of the pharmacists will be consumed quickly. In this study, we investigate on an association rule mining technology to improve efficiency in TCM dispensing based on the frequent pattern growth algorithm and try to identify which 2 or 3 herbal medicines will match together frequently in prescriptions. Furthermore, 3 experimental studies are conducted based on a dataset collected from a traditional Chinese medicine hospital. The dataset includes information for an entire year (2014), including 4 seasons and doctors. Afterward, a questionnaire on the usefulness of the extracted rules was administered to the pharmacists in the case hospital. The responses showed the mining results to be very valuable as a reference for the placement and ordering of the frames in the TCM pharmacies and drug stores. … (more)
- Is Part Of:
- Medicine. Volume 99:Issue 18(2020)
- Journal:
- Medicine
- Issue:
- Volume 99:Issue 18(2020)
- Issue Display:
- Volume 99, Issue 18 (2020)
- Year:
- 2020
- Volume:
- 99
- Issue:
- 18
- Issue Sort Value:
- 2020-0099-0018-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-05
- Subjects:
- association rule mining -- frequent pattern growth algorithm -- medicinal storage containers -- traditional Chinese medicine
Medicine -- Periodicals
Medicine -- Periodicals
Médecine -- Périodiques
Geneeskunde
Medicine
Periodicals
Periodicals
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http://journals.lww.com ↗ - DOI:
- 10.1097/MD.0000000000020090 ↗
- Languages:
- English
- ISSNs:
- 0025-7974
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- Legaldeposit
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