Million-Dollar Prize Hints at How Machine Learning May Someday Spot Cancer

A contest aimed at automating the detection of lung cancer shows how machine learning may be poised to overhaul medical imaging. The challenge offered $1 million in prizes for the algorithms that most accurately identified signs of lung cancer in low-dose computed tomography images. The winning algorithms won't necessarily be adopted by clinicians, but they could inspire algorithmic innovations that find their way into medical imaging. Low-dose CT scans have shown great potential in recent years for detecting lung cancer earlier. They use less radiation and do not require a contrast dye to be injected into the body.