mitjclinic/mirai repository overview

This container serves Mirai, the risk model described in: Towards Robust Mammography-Based Models for Breast Cancer Risk. Mirai was designed to predict risk at multiple time points, 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 US and was tested on held-out test sets from MGH, Karolinska in Sweden and Chang Gung Memorial Hospital in Taiwan, obtaining C-indices of 0.76 (0.74, 0.80), 0.81 (0.79, 0.82), 0.79 (0.79, 0.83), respectively. Mirai obtained significantly higher five-year ROC AUCs than the Tyrer-Cuzick model (p<0.001) and prior deep learning models, Hybrid DL (p<0.001) and ImageOnly DL (p<0.001), trained on the same MGH dataset. In our paper, we also demonstrate that Mirai was more significantly accurate in identifying high risk patients than prior methods across all datasets. On the MGH test set, 41.5% (34.4, 48.5) of patients who would develop cancer within five-years were identified as high risk, compared to 36.1% (29.1, 42.9) by Hybrid DL (p=0.02) and 22.9% (15.9, 29.6) by Tyrer-Cuzick lifetime risk (p<0.001).

The container launches a Flask web service, so clients can run predictions by POST-ing images. There is also a basic HTML web site which can be opened with a web browser. In either case, set host port to 5000.

Container source code: Ark⁠

Model source code: Mirai⁠