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Breast radiologist who co-developed the Mirai AI model that predicts breast cancer risk from a mammogram.
Constance Lehman co-led with Regina Barzilay the development and validation of Mirai, a deep-learning model that predicts five-year breast cancer risk from mammograms more accurately than clinical risk models across diverse populations, and led the ACRIN studies establishing MRI screening of the contralateral breast. She has led national breast imaging quality initiatives and now works on AI-driven personalised screening.
| Title | Journal | Year |
|---|---|---|
| Toward robust mammography-based models for breast cancer risk | Science Translational Medicine | 2021 |
| MRI evaluation of the contralateral breast in women with recently diagnosed breast cancer (ACRIN 6667) | NEJM | 2007 |
Shares Mammography & tomosynthesis, AI in radiology, HR-positive / HER2-negative breast cancer and the tags screening, ai, breast.
Shares AI in radiology, HR-positive / HER2-negative breast cancer and the tags screening, ai.
Shares Mammography & tomosynthesis and the tags screening, breast.
Shares Mammography & tomosynthesis, AI in radiology, HR-positive / HER2-negative breast cancer.
Shares Mammography & tomosynthesis, AI in radiology, HR-positive / HER2-negative breast cancer.
Shares Mammography & tomosynthesis, AI in radiology, HR-positive / HER2-negative breast cancer.
Shares Massachusetts General Hospital Cancer Center, Mammography & tomosynthesis, AI in radiology, HR-positive / HER2-negative breast cancer.
Shares Mammography & tomosynthesis, AI in radiology, HR-positive / HER2-negative breast cancer.