Using big data to identify triple-negative breast, oropharyngeal, and lung cancers

Researchers at Case Western Reserve University and colleagues used “big data” analytics to predict if a patient is suffering from aggressive triple-negative breast cancer, slower-moving cancers or non-cancerous lesions with 95 percent accuracy. If the tiny patterns they found in magnetic resonance images prove consistent in further studies, the technique may enable doctors to use an MRI scan to diagnose more aggressive cancers earlier and fast track these patients for therapy. Read more here.