TITLE : Machine learning for predicting cancer genotype and treatment response using digital histopathology images ABSTRACT : Computerized systems and methods for digital histopathology analysis are disclosed. In one embodiment, a series of deep learning networks are used that train, in succession, on datasets of successively increasing relevance. In some examples, learned parameters from at least a portion of one deep learning network are transferred to a next deep learning network in a succession of deep learning networks. In some examples, at least one of the deep learning networks includes a self-supervised learning network. In some examples, at least one of the deep learning networks includes an attention-based learning network. These and other examples and details are disclosed herein in various contexts including, for example evaluating genotypes of cancer tissue (e.g., bladder, prostate, or lung cancer) using histopathology images. In some examples, the context is to assist in predicting presence or absence of certain cancer genotypes and/or predicting patient responses to a new treatment.Classify the above INPUT TEXT into ONE OF these CATEGORIES ONLY (NO OTHER CATEGORIZATION SHOULD BE DONE):Brain Disorders, Cancer, Immunology & Inflammation,   Rare Blood Disorders, Rare Diseases,Vaccines,General Wellness,Infection. JUST GIVE CATEGORY NAME NO EXPLANATION IS REQUIRED Give two different versions of responses. Please separate the responses with 6 asterisk symbols: ******.
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