Personalized risk prediction for breast cancer pre-screening using artificial intelligence and thermal radiomics
作者：
Highlights：
• An affordable, non-invasive and radiation free personalized risk for breast cancer pre-screening.
• Machine learning over thermal images to generate a personalized risk score.
• 21 % (0.21) increase in AUC compared to age-based risk scoring.
• Risk stratification into 4 risk groups for screening guidance and early detection.
• Risk scoring even for dense breasts.
摘要
•An affordable, non-invasive and radiation free personalized risk for breast cancer pre-screening.•Machine learning over thermal images to generate a personalized risk score.•21 % (0.21) increase in AUC compared to age-based risk scoring.•Risk stratification into 4 risk groups for screening guidance and early detection.•Risk scoring even for dense breasts.
论文关键词：Breast cancer,Thermography,Risk assessment,Machine learning,Thermalytix,Artificial intelligence
论文评审过程：Received 10 September 2019, Revised 18 February 2020, Accepted 1 April 2020, Available online 7 April 2020, Version of Record 22 April 2020.
论文官网地址：https://doi.org/10.1016/j.artmed.2020.101854
