Mutual information mining for component law and development of new recipes of topical herbs for atopic dermatitis

Traditional Chinese medicines (CM) topical herbs for atopic dermatitis are mainly consist of nourishing the blood, dryness-moistening, dry-dampness, skin-moisturizing and itching-relief, of which therapeutic principles are taken as dryness-moistening to relieve itching. Based on the modified mutual information, complex system entropy cluster and unsupervised hierarchical clustering, the CM recipes for atopic dermatitis can be better collected and stored in the database, and the correlation coefficient between herbs, core combinations of herbs and new recipes also can be analyzed. In our study, the objective is to evaluate and analyze the component law of CM topical herbs and explore new recipes for atopic dermatitis through data mining methods so as to provide references for dermatologists in the clinical practice and decision-making for the treatment of atopic dermatitis.