Abstract
Cancer diagnosis and treatment rely on accurate identification of morphological, molecular, and genetic biomarkers. As technology and science progress, the number of biomarkers and testing required increases. Professional guidelines structure the biomarkers testing methodology. Yet, testing capabilities, options, and interpretation vary significantly between countries and medical centers in practice. Here, we present an alternative to the traditional methodologies for biomarker detection, using neural networks to detect the different biomarkers directly from hematoxylin and eosin (H&E) stained pathology slide images.
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