Traditional Drug (TM) has played a pivotal part in global healthcare, conceded for its literal practices and comprehensive approach to mending. At the same time, Artificial Intelligence (AI) has fleetly surfaced as a potent resource, able of recycling large datasets, relating trends, and supporting intricate decision- making tasks. The integration of these two fields — nominated Artificial Intelligence for Traditional Medicine (AITM) — presents fresh openings for advancements in healthcare.1 This review examines AITM from two primary perspectives developments in AI ways and their practical operations in TM. It emphasises the significance of Machine literacy, Deep Learning, and Large Language Models in colorful functions, including individual procedures (ahead, during, and after treatment) and exploration disciplines similar as medicine discovery, knowledge organisation, and data- driven analysis. The perpetration of AI methodologies.2
Ifat Shaikh*, Chetan Zaware, Kalyani Chande (2026) studied this question.