Exploring the Application of Knowledge Element Indexing in the Study of the Laws of Formula-Syndrome and Medicine-Syndrome with the Example of Categorized Collection of Medical Formulas: Emaciation-Thirst Disease

  OBJECTIVE  To explored the application of knowledge element indexing in the digitization of Chinese medical books by probing into the laws of formula-syndrome and medicine-syndrome in the Categorized collection of medical formulas: Emaciation-thirst disease.

  METHODS  The knowledge element indexing method was used to complete the depth indexing of the Categorized collection of medical formulas: Emaciation-thirst disease. In addition, The indexed data from the database was read. On top of that, the logical data of the derived formula and medicines was optimized, and the associations of the formula-syndrome and medicine-syndrome were visualized and analyzed via the construction of knowledge mapping.

  RESULTS  There were 616 knowledge bodies, 3 213 knowledge elements, 10 298 semantic meanings, and 4 369 semantic associations in the Categorized collection of medical formulas: Emaciation-thirst disease. The formula-syndrome knowledge mapping suggested that the main syndromes recorded in that chapter included thirsty with strong desire to drink, frequent urination, dry throat and tongue, as well as feverish sensations in palms, soles and chest, while the minor syndromes were emaciation, restlessness in the mind, white turbid urine, dysuria, excessive food intaking with rapid hungering, and dark urine. The study took the main syndromes as an example, and further overlapped and filtered them with the corresponding formula-medicine associations to obtain combination of formula associations for the treatment of "thirsty with strong desire to drink and restlessness in the mind". The combination of formula associations contained Qingxin Lianzi decoction, Damai decoction, Digupi beverage, Huanglian Zhudu pill, and Qingliangmi beverage. Besides, the nodes with high degree in medicine associations included snakegourd root, licorice root, dwarf lilyturf tuber, coptis rhizome, ginseng, common anemarrhena rhizome, astragalus root, and gypsum.

  CONCLUSION  The knowledge mapping analysis based on knowledge element indexing can not only show the association between formula-syndrome-medicine in a clear hierarchy, but also directly reveal the relationship between the core syndromes and the formulas used for treatment. Thus, the study has vital application value for digitization of Chinese medical books.