ArticleEvidence-based complementary and alternative medicine : eCAM2019
Selecting Effective Herbal Medicines for Attention-Deficit/Hyperactivity Disorder via Text Mining of Donguibogam.
Article in Evidence-based complementary and alternative medicine : eCAM, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Chinese herbal medicines for rhinosinusitis: a text-mining study with comparisons to contemporary research and clinical guidance.BMC complementary medicine and therapies · 2025Article
- Chinese Herbal Medicines for Rheumatoid Arthritis: Text-Mining the Classical Literature for Potentially Effective Natural Products.Evidence-based complementary and alternative medicine : eCAM · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveSeveral 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.
methodsText 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
conclusionsTwelve 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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.