Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer

@inproceedings{Vandenberghe2017RelevanceOD,
  title={Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer},
  author={Michel E. Vandenberghe and Marietta L. J. Scott and Paul W. Scorer and Magnus P. S{\"o}derberg and Denis Balcerzak and Craig Barker},
  booktitle={Scientific reports},
  year={2017}
}
Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous cases can affect diagnostic accuracy. Modern artificial intelligence methods such as deep learning have the potential to supplement pathologist expertise to ensure constant diagnostic accuracy. We developed a computational approach based on deep learning that automatically scores HER2, a biomarker that defines… CONTINUE READING
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