Large AI models are changing many parts of healthcare, but in TCM, genuinely valuable AI cannot rely on generic corpora and concepts alone. TCM emphasises syndrome differentiation, individual differences, four-diagnostic integration, medication feedback and follow-up adjustment. For AI to truly assist TCM physicians, the foundation must be high-quality, continuous, structured case data from real care.
Real case data is not just one chief complaint or one prescription. It should include the chief complaint, intake records, tongue and pulse, differentiation reasoning, prescription composition, medication changes, follow-up feedback, the adjustment process and staged results. Only when this information forms a continuous chain can a doctor-assistive system understand the real process of TCM care.
This means TCM model development cannot be detached from clinical settings, physician resources and compliant data governance. Without real physician care, a licensed internet hospital, fulfillment and follow-up, so-called TCM AI easily stays at knowledge Q&A or text generation, far from real clinical service.
Beijing Hongrun Kangyuan's data-technology direction is built on this logic. Grounded in a licensed internet hospital and real TCM physicians, and through remote pulse, tongue/face capture, intake systems and follow-up, it accumulates complete clinical case data and — under lawful authorisation, de-identification and data security — uses it for doctor-assistive tools, case structuring and TCM model training.
AI's positioning here is critical. AI is not a physician; it cannot diagnose independently or hold prescribing authority. The more reasonable role is an assistive tool: helping organise patient information, suggesting follow-up questions, assisting case structuring, providing differentiation reference and improving follow-up efficiency — all under the physician's final judgement.
From a compliance view, the greater the value of medical data, the higher the bar for data security and personal-information protection. Patient authorisation, data minimisation, de-identification, access control, audit trails, secure storage and compliance auditing all matter before data enters research, model training or external cooperation. Any use that skips compliance can pose major risk to enterprises and partners.
This is a data-compliance observation; company practices are cited as examples and do not constitute medical advertising or efficacy claims.
This article is a compliance-reviewed publication by Hongrun Kangyuan and does not constitute medical, investment or legal advice. Clinical references are intended for medical professionals only.
