학술논문
Thai Herbs Recommendation Model
Document Type
Conference
Source
2024 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON) Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON), 2024 Joint International Conference on. :515-518 Jan, 2024
Subject
Language
ISSN
2768-4644
Abstract
This work proposes a Thai herbs recommendation model to recommend appropriate Thai herbs to users. Herbs data was collected from available data sources including books, websites, and publication documents. All data were integrated, cleaned, and transformed before transfer to the herbs database. The rule-based was produced based on herbs properties for various symptoms. Then, the best Thai herbs were given based on the specific condition of the user. The overall model evaluation was compared with solutions from the National List of Essential Drugs A.D. 1999 (List of herbal medicine products) given 0.77 precision, 1.00 recall, and 0.87 F-measure.