Development of database structure and indexing for siddha medicine system – A platform for siddha literature analytics
Authors
Dhivya Karmegam
aSchool of Public Health, SRM University, Kattankulathur 603 203, Kancheepuram District, Tamil Nadu, India
Muthuperumal Prakash
aSchool of Public Health, SRM University, Kattankulathur 603 203, Kancheepuram District, Tamil Nadu, India
N Karikalan
cNational Institute for Research in Tuberculosis, Chetpet, Chennai 600 031, Tamil Nadu, India
Bagavandas Mappillairajan
bCentre for statistics, SRM University, Kattankulathur 603 203, Kancheepuram District, Tamil Nadu, India
Keywords:
Traditional medicine, Database management system, Siddha, MySQL workbench, Machine learning
Abstract
Siddha Medicine system is one among the oldest traditional systems of medicines in India and has its entire literature in the Tamil language in the form of poems (padal in tamil). Even if the siddha poems are available in public domain, they are not known to other parts of the world because, researchers of other languages are not able to understand the contents of these poems and there exists a language barrier. Hence there is a need to develop a system to extract structured information from these texts to facilitate searching, comparing, analysis and implementing.
Objective
This study aimed at creating a comprehensive digital database system that systematically stores information from classical Siddha poems and to develop a web portal to facilitate information retrieval for comparative and logical analysis of Siddha content.
Methods
We developed an expert system for siddha (eSS) that can collect, annotate classical siddha text, and visualizes the pattern in siddha medical prescriptions (Siddha Formulations) that can be useful for exploration in this system using modern techniques like machine learning and artificial learning. eSS has the following three aspects: (1) extracting data from Siddha classical text (2) defining the annotation method and (3) visualizing the patterns in the medical prescriptions based on multiple factors mentioned in the Siddha system of medicine. The data from three books were extracted, annotated and integrated into the developed eSS database. The annotations were used for analyzing the pattern in the drug prescriptions as a pilot work.
Results
Overall, 110 medicinal preparations from 2 Siddhars (Agathiyar and Theran) were extracted and annotated. The generated annotations were indexed into the data repository created in eSS. The system can compare and visualize individual and multiple prescriptions to generate a hypothesis for siddha practitioners and researchers.
Conclusions
We propose an eSS framework using standard siddha terminologies created by WHO to have a standard expert system for siddha. This proof-of-concept work demonstrated that the database can effectively process and visualize data from siddha formulations which can help students, researchers from siddha and other various fields to expand their research in herbal medicines.
Keywords: Traditional medicine, Database management system, Siddha, MySQL workbench, Machine learning
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