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(Dartmouth-Hitchcock Medical Center) Dartmouth scientists have proposed a new machine learning model for identification of esophageal cancer that could open new avenues for applying deep learning to digital pathology. The novel method automatically learns clinically important regions on whole-slide images for classification. The approach outperformed the current state-of-the-art model that requires detailed, manual annotations by a pathologist for its training. Such systems could assist pathologists in reading slides more accurately and efficiently while eliminating laborious, high-cost data annotation.NEXT ARTICLE
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Standard antiretroviral therapy (ART) consists of the combination of at least three antiretroviral (ARV) drugs to maximally suppress the HIV virus and stop the progression of HIV disease. Huge reductions have been seen in rates of death and suffering whe...