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Image/AI-driven Cancer Biomarker to Measure Immune Environment
An image-based biomarker for quantifying tumour-infiltrating lymphocyte score in histopathological samples using proprietary AI technologies

Background
Digital pathology is an emerging field. It uses sophisticated computing tools and artificial intelligence (AI) to diagnose disease and guide treatments faster and more easily. It offers particular promise for developing novel ways to understand cancer.
The Computational Pathology and Integrative Genomics Team at The Institute of Cancer Research, London, has already created a method to automate tumour-infiltrating lymphocyte (TIL) scoring in several cancer types, by scanning routine pathological slides into digital images and using an AI algorithm to analyse the images automatically at the single-cell level. They are currently adapting and trialling this algorithm for use as a novel biomarker.
Triple-Negative Breast Cancers (TNBC) are among the most aggressive forms of breast cancer but there are too few
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