Breast cancer risk prediction model based on C5.0 algorithm for postmenopausal women Breast cancer is one of the most common malignant tumors of women in the world, and it most happen in the elderly women, but in recent years the age of onset has become younger. As we know that, postmenopausal women are the groups with less research on breast cancer, and the characteristics of breast cancer are still to be explored. In this paper, based on the characteristic of 1031 postmenopausal women (xe2xa9xbe43 years old) breast cancer data, a breast cancer risk prediction model based on C5.0 algorithm was constructed and the model was optimized. The experimental results show that: a) Compared with machine learning methods such as neural network and support vector machine, C5.0 algorithm has better performance in constructing breast cancer risk prediction model; b) Costmatrix_C5.0 Model with cost matrix is better than adaptiveboosting_c5.0 model with Adaptive Enhancement algorithm; c) The risk of breast cancer is strongly correlated with postmenopausal hormones, age, age of menopause, history of benign breast disease and age of the first childbearing. This research is a practical application of data mining in the medical field and has certain reference value for the clinical diagnosis of breast cancer.

Medication Rules of Traditional Chinese Medicine in Consolidation Period of Breast Cancer Based on Association Rules Mining Objective: To explore the association rules between medicines, core combinations and new prescriptions, and to analyze the medication rules of traditional Chinese medicine(TCM) in consolidation period of breast cancer based on data mining of medical records of TCM treatment in consolidation period of breast cancer in outpatient clinic of Hunan University of TCM in recent 10 years. Method: Use Python 3.7 software to select association rule algorithm with the minimum support degree greater than 60% and the minimum confidence greater than 0.9 to conduct data mining of the collected medical records. Results: A total of 9739 medical records and 178 Chinese herbal medicines were selected for data mining. The TCMs with higher frequency are atractylodes macrocephala, astragalus membranaceus, poria cocos, codonopsis pilosula, coix seed, hedyotis diffusa and scutellaria barbata. The top five bilinked medicines in confidence are scutellaria barbata with atractylodes macrocephala, hedyotis diffusa with atractylodes macrocephala, liquorsaturated ligustrum lucidum with atractylodes macrocephala, coii with atractylodes macrocephala, and poria cocos with atractylodes macrocephala. The top five triplelinked medicines in confidence are liquorsaturated ligustrum lucidum with scutellaria barbata with atractylodes macrocephala, poria cocos with coix seed with atractylodes macrocephala, liquorsaturated ligustrum lucidum with coix seed with atractylodes macrocephala, and poria cocos with scutellaria barbata with atractylodes macrocephala. The top five quadrlinked medicine in confidence are poria cocos with liquorsaturated ligustrum lucidum with coix seed with atractylodes macrocephala, poria cocos with liquorsaturated ligustrum lucidum with scutellaria barbata with atractylodes macrocephala, hedyotis diffusa with poria cocos with liquorsaturated ligustrum lucidum with atractylodes macrocephala, codonopsis pilosula with poria cocos with liquorsaturated ligustrum lucidum with astragalus membranaceus, and codonopsis pilosula with atractylodes macrocephala with liquorsaturated ligustrum lucidum with astragalus membranaceus. Conclusion: The main pathogenesis of consolidation period of breast cancer is Qi deficiency and toxin stagnation, and the most important treatment is enriching Qi and detoxify, strengthening the spleen and tonifying the kidney.