Authors: Rasika Kokate, Saloni Gohad, Vaishnavi Gulave, Tanuja Karpe, Sunita Borse
Abstract: AYUSH (Ayurveda Yoga Naturopathy Unani Siddha and Homeopathy) system is a repository of the wisdom obtained from 8000 plants. But most of this knowledge is available in printed and handwritten Sanskrit and Hindi manuscripts which are computing unfriendly. This study introduces an end-to-end AYUSH knowledge recommendation pipeline based on AI to digitize, interpret and recommend insights from the AYUSH body of knowledge for modern computational intelligence. The framework combines Optical Character Recognition (Tesseract OCR), NLP for Indic languages, Knowledge Graph modelling (Neo4j) and AI-based reasoning (BERT, Random Forest) to convert unstructured manuscripts into searchable knowledge that can be analyzed by human . The system captures herbal, disease and treatment entities, relates the entities semantically, and then provides query-driven recommendations through an intelligent interface. Using a simple interface, researchers would be able to ask for insights such as “What are the herbs that have been associated with anti-inflammatory activity?” This strategy lowers the expense of early stage drug discovery, validates traditional remedies, and forges new roads in integrated health care investigation. This study provides the infrastructure for AI- based analysis of literature on traditional medicine and adds to digital conservation, availability and edification as well as evidence-informed integrated healthcare.
DOI: http://doi.org/10.5281/zenodo.20786139
