Abstract： Objective This study aims to explore the medication rules of traditional Chinese medicine(TCM)oral prescriptions for skin cancer based on data mining,providing reference for TCM treatment of skin cancer.Methods TCM prescriptions that meet the screening criteria were entered into the Excel 2021 database to establish a database.The properties,flavors,and meridians of the involved TCM were statistically analyzed.IBM SPSS Modeler 18.0 was used for core TCM association rule analysis.IBM SPSS Statistic 24.0 software was utilized for core TCM clustering analysis and factor analysis.Results 59 included TCM prescriptions contains 162 Chinese medicines,which were used 702 times in total.The majority of the TCM were cold in nature,bitter in taste,and belonged to the liver meridian.The next most common were warm in nature,sweet and spicy in taste,and belonged to the spleen-stomach and lung meridians.The 16 core TCM were classified into 5 categories based on their functions,including tonifying deficiency herbs such as licorice,astragalus,angelica;heat-clearing herbs such as honeysuckle and scutellaria;diuretic and dampness-dispelling herbs such as poria and coix seed;blood-activating and stasis-resolving herbs such as chuanxiong and qi-regulating drugs such as tangerine peel.The highest support association rules included"licorice-astragalus""astragalus-angelica-licorice""astragalus-tuckahoe-angelica-licorice"and so on.Four clustered prescriptions were obtained through core TCM clustering analysis,and seven common factors were extracted through factor analysis.Conclusion TCM oral treatment for skin cancer should consider using tonifying deficiency herbs such as angelica and astragalus,heat-clearing herbs such as honeysuckle and scutellaria and dampness-dispelling herbs such as poria and coix seed,and blood-activating and stasis-resolving herbs such as chuanxiong.It is important to adhere to the principle of"treating the syndrome with corresponding medicine"and use TCM prescriptions based on individualized pattern differentiation.