In the last few years, research has shown that deep learning can match expert-level performance in medical imaging tasks like early cancer detection and eye disease diagnosis. But there’s also cause for caution. Other research has shown that deep learning has a tendency to perpetuate discrimination. With a health-care system already riddled with disparities, sloppy applications of deep learning could make that worse.
Now a new paper published in Nature Medicine is proposing a way to develop medical algorithms that might help reverse, rather than exacerbate, existing inequality.
