Computers trounce pathologists in predicting lung cancer type, severity
Tuesday, August 16, 2016 - 07:32
in Health & Medicine
Computers can be trained to be more accurate than pathologists in assessing slides of lung cancer tissues, according to a new study by researchers at the Stanford University School of Medicine. 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 […]