@article {10.3844/jcssp.2017.175.183,
article_type = {journal},
title = {A Framework for Systematizing Personalized Thai Herbal Medicine: A Case Study Covering Gynecological Conditions},
author = {Prompukdee, Charinee and Rungrattanaubol, Jaratsri and Pratoomsoot, Chayanin},
volume = {13},
number = {6},
year = {2017},
month = {Jun},
pages = {175-183},
doi = {10.3844/jcssp.2017.175.183},
url = {https://thescipub.com/abstract/jcssp.2017.175.183},
abstract = {Thai Traditional Medicine (TTM) is an integral part of Thai traditional culture, with a history which spans many centuries. As part of this tradition, a significant number of historical pharmacopoeias and herbal textbooks have been preserved but much of the content of these texts is hard to access and interpret and so this paper proposes a framework for applying  knowledge management processes to TTM. The outcome of this is the design and development of a system for making personalized prescriptions of Thai herbal medicines. By extracting and capturing knowledge from the TTM text 'Pra Kampee Maha-Chotarat' (an ancient text on the subject of gynecological conditions) and through consulting with TTM experts, a system was developed to support TTM consultants when making individual prescriptions for traditional medicines. The association rule mining technique was used to obtain recommended herbal compositions and the system was evaluated by experts, who gave feedback on the design, content and usage of the system. The proposed framework and system has the potential to be extended to cover the treatment of other diseases by drawing data from other TTM texts.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}