Computers trounce pathologists in predicting lung cancer type, severity, researchers find

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.