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"The amount of data in pathology images has previously been too vast for researchers to process easily, but that's changing thanks to advanced machine learning. A group of researchers from Stanford University were able to more accurately predict lung cancer prognoses by grabbing images from the Cancer Genome Atlas from patients with the disease and then through those train a computer software program to pinpoint characteristics in the images previously unable to be seen by the human eye.", www.fiercehealthcare.com
"Computers can be trained to be more accurate than pathologists in assessing slides of lung cancer tissues, according to a new study. The researchers found that a machine-learning approach to identifying critical disease-related features accurately differentiated between two types of lung cancers and predicted patient survival times better than the standard approach of pathologists classifying tumors by grade and stage.", www.sciencedaily.com
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