Reporters learned from Guangdong Provincial People's Hospital on the 10th that Professor Wang Kun of the Breast Cancer Department of the hospital led the development of a non-invasive artificial intelligence system, which can early predict the load of residual tumors after neoadjuvant chemotherapy for breast cancer. The research system has recently been included in the international journal Yearbook of Surgery. At present, residual tumor burden (RCB) classification has become one of the generally recognized criteria for evaluating the efficacy of neoadjuvant therapy for breast cancer. This standard comprehensively evaluates the treatment response of patients by measuring parameters such as the range of primary cancer lesions, cancer cell density, number of positive lymph nodes, and maximum diameter of lymph node cancer lesions after neoadjuvant chemotherapy. The lower the RCB rating, the better the treatment effect. RCB-0 indicates that breast cancer has achieved complete pathological remission, and RCB-3 indicates that breast cancer is resistant to treatment. Therefore, identifying RCB-3 patients in the early stage of neoadjuvant chemotherapy can help doctors adjust the chemotherapy regimen in a timely manner, develop appropriate surgical and follow-up strategies for patients, and is of great significance for clinical decision-making. However, in current clinical practice, there is still a lack of a tool that can predict RCB grading in an early non-invasive manner. In view of this situation, Wang Kun and his team built the world's first artificial intelligence system for different molecular subtypes of breast cancer with magnetic resonance imaging as the entry point and magnetic resonance data from multi center breast cancer patients, which can accurately predict the RCB grade of breast cancer at the early stage of neoadjuvant chemotherapy. This artificial intelligence system can not only accurately predict patients with good therapeutic effects at RCB-0-1 level, but also early identify patients with chemotherapy failure at RCB-3 level. "This scientific research progress can not only assist doctors to adjust neoadjuvant chemotherapy schemes and determine the timing of surgery, but also promote the accuracy of breast cancer treatment, which is expected to provide patients with more personalized surgery and nursing hierarchical management, and can maximize the avoidance of toxic side effects of chemotherapy, reduce the economic burden of patients, which has great value in clinical practice." Wang Kun said. (Lai Xin She)