Review: Predictive approaches to breast cancer risk

作者：Huang, Shuai; Xu, Jun Tao; Yang, Mei^*

来源：Heliyon, 2023, 9(11): e21344.

DOI：10.1016/j.heliyon.2023.e21344

• Breast cancer
• Risk factors
• BRCA1/2
• Polygenic risk scores
• Artificial intelligence

Despite the deployment of specific breast cancer screening strategies, breast cancer incidence rates have escalated significantly over recent decades. In a bid to reverse this trend, scientists have engaged in extensive epidemiological research into breast cancer prevalence, identifying numerous individual risk factors and promoting population-wide health education. Coupled with advances in genetic testing, risk prediction models based on breast cancer genes have been developed, albeit with inherent limitations. In the new millennium, the emergence of artificial intelligence (AI) as a dominant technological force suggests that breast cancer prediction models developed with AI may represent the next frontier in research.

• 单位
  南方医科大学; 中国科学院; 广东省人民医院