ABSTRACT
Objective: To analyze the composition regularities of the traditional Chinese medicine formulas (TCMFs) for treating five kinds of ophthalmic diseases, including swelling and pain of eyes, night blindness, pterygium, blepharitis marginalis and nebula based on the data mining methodology. Methods: A total of 1999 TCMFs for ophthalmic diseases were collected from the Dictionary of Chinese Medicine Prescriptions. Then frequency analyses and association rules analyses were conducted with the three indicators of support, confidence and lift based on the Apriori algorithm. Results: The diaphoretic drugs and heat-clearing drugs were the commonly used types of the traditional Chinese medicines (TCMs) for swelling and pain of eyes, pterygium and blepharitis marginalis. The heat-clearing drugs and tonifying drugs were the commonly used types of TCMs for night blindness and nebula. Coptidis Rhizoma was frequently used for swelling and pain of eyes, Schizonepetae Herba was for blepharitis marginalis, and Chuanxiong Rhizoma was for nebula. The latent association rules with significant lift included Margarita→Calamina for swelling and pain of eyes, Myrrha→Olibanum for pterygium, Notopterygii Rhizoma et Radix→Saposhnikoviae Radix for blepharitis marginalis, and Lithargite→Sal Ammoniac for nebula. Conclusion: Using association rules, the comparative study on the five kinds of ophthalmic diseases can reveal the similarities and differences of treatments for these ophthalmic diseases and explore the composition regularities of TCMs, which helps to explore the hidden value of TCMFs.
ABSTRACT
To study and compare the medication regularities of traditional Chinese medicine formulas(TCMFs) for the six kinds of pains,namely abdominal pain,headache,epigastric pain,hypochondriac pain,heartache and backache,using a data-mining approach,in order to provide reference for relevant studies for the compatibility mechanism and new compound development of related TCMFs. A total of 2 443 TCMFs for pains were collected from the Dictionary of Chinese Medicine Prescriptions,and analyzed using the Apriori algorithm based on three indicators,namely confidence,lift and support,so as to study pivotal traditional Chinese medicines(TCMs) for each pain and their compatibility regularities. The results showed that deficiency tonifying medicines(such as Glycyrrhizae Radix et Rhizoma and Angelicae Sinensis Radix),Qi-regulating medicines(like Aucklandiae Radix) and blood circulation promoting medicines(like Chuanxiong Rhizoma) were commonly used TCMs for pains. However,there were many differences between drugs for various kinds of pains. For example,Magnoliae Officinalis Cortex was used frequently for abdominal pain and epigastric pain,while Saposhnikoviae Radix was used frequently for headache. The latent association rules with significant lift included Carthami Flos → Angelicae Sinensis Radix for abdominal pain,Astragali Radix → Glycyrrhizae Radix et Rhizoma for headache,Hordei Fructus Germinatus → Citri Reticulatae Pericarpium for epigastric pain,Gentianae Radix et Rhizoma → Bupleuri Radix for hypochondriac pain,and Caryophylli Flos → Moschus for backache. This study showed that based on the TCMFs from the Dictionary of Chinese Medicine Prescriptions,the data-mining approach can reveal the differences and similarities in the use of TCMs for the six kinds of pains,and discover the latent composition regularities of relevant TCMs.