Deep learning model to predict Ki-67 expression of breast cancer using digital breast tomosynthesis.

Ken ObaMaki AdachiTomoya KobayashiEichi TakayaDaiki ShimokawaToshinori FukudaKengo TakahashiKazuyo YagishitaTakuya UedaHiroko Tsunoda

Published in: Breast cancer (Tokyo, Japan) (2024)

Our results suggest the potential application of our DL model to predict the expression of Ki-67 using DBT, which may be useful for preoperatively determining the treatment strategy for breast cancer.

Keyphrases

poor prognosis
deep learning
neoadjuvant chemotherapy
binding protein
machine learning
magnetic resonance imaging
long non coding rna
lymph node
risk assessment
convolutional neural network
breast cancer risk
climate change