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Found 5 papers, 2 papers with code
Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging
Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment.
Difficulty Translation in Histopathology Images
Our model comprises a scorer, which provides an output confidence to measure the difficulty of images, and an image translator, which learns to translate images from easy-to-classify to hard-to-classify using a training set defined by the scorer.
Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification
Based on the nature of histopathology images, a range of difficulty inherently exists among examples, and, since medical datasets are often labeled by multiple annotators, annotator agreement can be used as a natural proxy for the difficulty of a given example.
Patient level simulation and reinforcement learning to discover novel strategies for treating ovarian cancer
The prognosis for patients with epithelial ovarian cancer remains dismal despite improvements in survival for other cancers.
Identifying and mitigating bias in algorithms used to manage patients in a pandemic
Numerous COVID-19 clinical decision support systems have been developed.
