ProFound AI Risk

ProFound AI risk is a clinical decision support tool that provides personalized one-, two-, and three-year breast cancer risk estimates based on 2D screening mammograms or 3D breast tomosynthesis. ProFound AI Risk combines a range of risk factors (age, density, subtle mammographic features) to produce short-term risk assessments that physicians can use to create customized screening plans and catch early-stage cancers.
Information source: Vendor
Last updated: Dec. 19, 2023

General Information

Product name ProFound AI Risk
Company iCAD
Subspeciality Breast
Modality Mammography
Disease targeted Breast cancer
Key-features Individual 1y/2y/3y breast cancer risk score
Suggested use During: report suggestion

Technical Specifications

Data characteristics
Population Asymptomatic screening population
Input 2D Mammography, 3D Digital Breast Tomosynthesis, age of patient
Input format DICOM
Output Risk score
Output format DICOM SR, GSPS
Integration Integration in standard reading environment (PACS), Stand-alone third party application
Deployment Locally on dedicated hardware
Trigger for analysis Automatically, right after the image acquisition
Processing time 1 - 10 minutes


Certified, Class I , MDD
FDA No or not yet
Intended Use Statements
Intended use (according to CE) The ProFound AI Risk clinical decision support tool is intended to be used by physicians to estimate a woman’s risk of developing breast cancer within a short timeframe of her normal mammogram. The tool is designed to inform and support physicians in their decision making process of personalizing screening or follow-up testing.


Market presence
On market since 07-2020
Distribution channels iCAD inc, RMS Medical Devices (Benelux), Sectra Amplifier Store
Countries present (clinical, non-research use) -
Paying clinical customers (institutes) >1
Research/test users (institutes) >1
Pricing model
Based on


Peer reviewed papers on performance

  • European validation of an image-derived AI-based short-term risk model for individualized breast cancer screening—a nested case-control study (read)

  • A risk model for digital breast tomosynthesis to predict breast cancer and guide clinical care (read)

  • Identification of women at high risk of breast cancer who need supplemental screening (read)

Non-peer reviewed papers on performance
Other relevant papers