Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients

HIGHLIGHTS

SUMMARY

There have been no studies using deep learning that combine whole breast MRI, DCE MRI dynamics, MRI at multiple treatment time points, and inclusion of non-imaging data to predict RCB and PFS. PCR Although many studies have reported machine_learning methods to predict PCR (see reviews ), only a few studies used deep learning on whole MRI images as inputs to predict PCR. There are a few studies that have used logistic regression and supervised machine_learning methods to predict RCB. Tahmassebi et_al evaluated a few supervised machine_learning methods (including support vector machine (SVM), linear regression . . .

 



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