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Machine learning can help predict patient response to cancer immunotherapy

Machine learning algorithm predicts a tumor s response to immune checkpoint blockade

Full Genetic Architecture of RAS Cancer Gene Mutations in Human Tumors Uncovered

Full Genetic Architecture of RAS Cancer Gene Mutations in Human Tumors Uncovered
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Astronomy meets pathology to identify predictive biomarkers for cancer immunotherapy

 E-Mail IMAGE: The AstroPath platform allows for the assessment of the level of expression of a given marker on individual cells, while maintaining information on their spatial location. Shown here is. view more  Credit: Seyoun Park, Ph.D. Pairing sky-mapping algorithms with advanced immunofluorescence imaging of cancer biopsies, researchers at The Mark Foundation Center for Advanced Genomics and Imaging at Johns Hopkins University and the Bloomberg~Kimmel Institute for Cancer Immunotherapy developed a robust platform to guide immunotherapy by predicting which cancers will respond to specific therapies targeting the immune system. A new platform, called AstroPath, melds astronomic image analysis and mapping with pathology specimens to analyze microscopic images of tumors.

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