Breast Cancer Cope: Early diagnosis and artificial intelligence applications

Breast cancer is one of the most common cancers in the world and the leading cause of death among women. Knowledge of breast cancer is essential for early detection and treatment.The incidence of breast cancer is linked to a number of factors, such as genetic factors, lifestyle, hormone levels, etc. Some genetic mutations are closely related to the susceptibility of breast cancer, with women with family history at a relatively high risk of morbidity. In addition, chronic high-fat diets, alcohol consumption, lack of exercise and long-term exposure to estrogens may increase the incidence of disease.Early detection of breast cancer is essential to improve the survival of patients. At present, there are three main methods of routine video screening for mammography: mammography, breast ultrasound and mammography MRI.Breast X-ray is one of the most widely used tools for early detection of breast cancer, with the advantages of cost-effective, simple operations and speed of treatment, and is the most commonly used screening method for female breast cancer screening worldwide. However, subjective interpretations of mammography by radiologists may vary, and dual reading, while increasing diagnostic sensitivity, may reduce work efficiency and increase the results of false positive examinations.Breast ultrasound, because it is not radioactive, is applicable at all ages, especially for pregnant and lactating women. The diagnostic performance of radiologists in identifying early breast cancer and reducing the number of unnecessary biopsies can be significantly improved through techniques such as smart multi-module cutting-wave elastic imaging.The advantage of mammography MRI is that it is non-irradiated and has a high soft tissue resolution and can be detected more sensitively. In-depth studies based on MRI images have the potential to improve the diagnostic accuracy of breast cancer, and dynamic enhanced screening can also help to identify benign and malignant diseases [1].In recent years, as computer performance has increased rapidly, artificial intelligence has played an increasingly important role in breast cancer video treatment. Artificial intelligence combined mammography tests provide unprecedented opportunities for breast cancer treatment. In breast X-ray photography, an in-depth learning model improves the accuracy of breast cancer detection; in breast ultrasound, an assistor improves the effectiveness of diagnosis; and in breast MRI, it helps to identify the disease accurately. In addition, in-depth learning-based genetic models can predict the risk of breast cancer and guide patients to individualized prevention and treatment.While artificial intelligence technologies have great potential for breast cancer treatment, they also face challenges such as data privacy protection, algorithm interpretability, clinical utility, etc. In the future, we look forward to further improvements in the level of care for breast cancer through the integration of multi-mode data, the optimization of in-depth learning models, the promotion of individualized medical models, the optimization of health-care resources and the strengthening of international cooperation, so as to provide better medical care and quality of life for patients.Female friends should be concerned about their own breast health, and regular breast screenings should be conducted, and in case of exceptional and timely medical treatment. At the same time, maintaining a healthy lifestyle is important for preventing breast cancer.References:[1] Progress in research by Tianwu, Zhang Min Wei, Li De Chun. J]. Molecular Image Journal, 2024, 47 (09): 1003-1006.