Selecting Effective Herbal Medicines for Attention-Deficit/Hyperactivity Disorder via Text Mining of Donguibogam

Autor: Hyo Won Bae, Se Yeon Lee, Sung Ji Kim, Jin Ung Baek, Byung Tae Choi, Hwa Kyoung Shin
Rok vydání: 2019
Předmět:
Zdroj: Evidence-Based Complementary and Alternative Medicine, Vol 2019 (2019)
Evidence-based Complementary and Alternative Medicine : eCAM
ISSN: 1741-4288
1741-427X
DOI: 10.1155/2019/1798364
Popis: Objective. Several attempts have been made to reduce the harmful side effects and increase the efficacy of current drugs used to treat attention-deficit/hyperactivity disorder (ADHD). Many articles have studied medicinal herbs as an effective supplement in treating ADHD. In a similar manner, this study provides foundational data to identify herbs that are potentially effective in treating ADHD by text mining of Donguibogam, which is a comprehensive summation of the important traditional principles and practices of Korean medicine.Methods. Text mining was performed for 3833 herbal prescriptions and 1108 medicinal herbs comprising prescriptions listed in Donguibogam. The first step was frequency analysis followed by chi-square test, which is a statistical hypothesis test.Results and Conclusions. Twelve medicinal herbs were selected for each ADHD subtype: hyperactivity ADHD type (ADHD-PHI) and attention-deficit ADHD type (ADHD-PI). Compared to previous research on traditional literature, a newer and more efficient methodology of selecting herbal medicines was developed in this process.
Databáze: OpenAIRE
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