Exploring the power of data mining for uncovering traditional medicinal plant knowledge: A case study in Shahrbabak, Iran.

ABSTRACT: The present study recorded indigenous knowledge of medicinal plants in Shahrbabak, Iran. We described a method using data mining algorithms to predict medicinal plants' mode of application. Twenty-oneindividuals aged 28 to 81 were interviewed. Firstly, data were collected and analyzed based on quantitative indices such as the informant consensus factor (ICF), the cultural importance index (CI), and the relative frequency of citation (RFC). Secondly, the data was classified by support vector machines, J48 decision trees, neural networks, and logistic regression. So, 141 medicinal plants from 43 botanical families were documented. Lamiaceae, with 18 species, was the dominant family among plants, and plant leaves were most frequently used for medicinal purposes. The decoction was the most com

SUBMITTER: Bibak H 

PROVIDER: S-EPMC11164334 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature