Hypothesis‐free deep survival learning applied to the tumour microenvironment in gastric cancer
Abstract The biological complexity reflected in histology images requires advanced approaches for unbiased prognostication. Machine learning and particularly deep learning methods are increasingly applied in the field of digital pathology. In this study, we propose new ways to predict risk for cance...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-10-01
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| Series: | The Journal of Pathology: Clinical Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/cjp2.170 |