Letter re: Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review

We were very interested to read the recent review article by Schneider et al. [1] who emphasised that innovations in cancer diagnostics and therapy are urgently required. Those authors analysed 11 studies aimed to enhance cancer diagnostics by combining molecular omics data with image analysis of haematoxylin and eosin (H&E)-stained slides of tumour tissue. The analysis of H&E-stained slides is a gold standard in cancer diagnosis, and it is a time-consuming process for pathologists and presents a major challenge to develop methods for automated analysis.

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