It is important to identify the right women to refer to supplemental screening to reduce the rates of under- or over-diagnosis. Densitas riskai supports the identification of higher-risk women who may benefit from supplemental imaging.
The reliance on image features standardizes risk estimates and reduces biases that are associated with traditional risk models introduced by the use of subjective information.
Automated short-term breast cancer risk assessment leverages image features as data input sources as opposed to traditional risk models that incorporate extensive patient history that is time-consuming to collect and susceptible to poor reliability, reproducibility, and precision.
Aligns with CAR guidance on triaging higher-risk women for follow-up imaging factoring in breast density, allowing doctors and patients to make informed decisions regarding further imaging.