Interpretable Tumor Localization in Bladder Cancer Histopathology Using Deep Multiple Instance Learning
Deep learning has emerged in cancer histopathology as a tool for predicting clinical and molecular properties of a patient’s disease, thereby connecting slide with function. This concept is especially relevant to bladder cancer, where molecular and histopathologic heterogeneity is known to impact on...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/145102 |