Recognized in the Harvard Business Review as an innovative A.I. solution for supporting improved clinical outcomes in breast cancer screening.
Automated Rapid Risk Assessment
Automated short-term risk assessment uses only DICOM images as data input sources as opposed to traditional risk models that incorporate patient clinical history that is time-consuming to collect and requires integration with multiple information systems.
Eliminate Subjectivity in Risk Assessment
The use of data from DICOM images alone standardizes risk estimates and reduces biases that are associated with traditional risk models introduced by the use of subjective information.
Worklist Generation and Study Assignment
Quick filtering and sorting of studies by automated and standardized rapid risk assessments can be used to identify patients for follow-up imaging exams and to optimally assign studies to particular readers or groups of readers.
Risk Categorization in Alignment with ACR Guidance
Aligns with ACR 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.