Using AI to Detect Cancer, Not Just Cats
Shaokang Wang and his startup, Infervision, build algorithms that read X-ray images and identify early signs of lung cancer. And just last week, the data science competition site Kaggle announced the winners of a $1 million contest in which more than 10,000 researchers competed to build machine learning models that could detect lung cancer from CT scans. Deploying such AI on a large scale—across hospitals, for instance—is still enormously difficult, says Dr. George Shih, a physician and professor at Weill Cornell Graduate School of Medical Sciences, and the co-founder of MD.ai, a company that participated in the Kaggle contest. Shih's company aims to build services for collecting and labeling data that researchers and companies can then use to train neural networks, not just for cancer detection but for many other tasks as well. Over the next few years, he says, researchers aren't likely to build an AI that's better at detecting lung cancer than the very best doctors.












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