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About
Accurate risk assessment is essential for the success of population screening programs and early detection efforts in breast cancer. Mirai is a new deep learning model based on full resolution mammograms.
Mirai is a mammography-based deep learning model designed to predict risk at multiple timepoints, leverage potentially missing risk factor information, and produce predictions that are consistent across mammography machines. Mirai was trained on a large dataset from Massachusetts General Hospital (MGH) in the United States and found to be significantly more accurate than the Tyrer-Cuzick model, a current clinical standard.
The primary aim of this study is to prospectively quantify the clinical benefit (i.e. MRI/CEM cancer detection rate) of Mirai-based guidelines and to compare them to the current standard of care.
Enrollment
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Inclusion criteria
Women who were identified as high risk on the retrospective study (dating from 2017-2025) using MIRAI will be recruited and consented for the prospective study
Women over 40 years of age identified as high risk according to traditional guidelines will also be potentially eligible for this study
Following consent and enrollment in the study, a participant will subsequently receive the following:
To be selected, a given record must include the following:
Exclusion criteria
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Interventional model
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200 participants in 2 patient groups
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Central trial contact
Sara Schiller, MPH
Data sourced from clinicaltrials.gov
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