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We trained an algorithm to detect cancer in just two hours

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Guest Nicole

Doctors across the world are beginning to rely on artificial intelligence algorithms to help accelerate diagnostics and treatment plans, with the goal of making more time to see more patients, with greater precision. We all can understand—at least conceptually—what it takes to be a doctor: years of medical school lectures attended, stacks of textbooks and journals read, countless hours of on-the-job residencies. But the way AI has learned the medical arts is less intuitive.

In order to get more clarity on how algorithms learn these patterns, and what pitfalls might still lurk within the technology, Quartz partnered with Leon Chen, co-founder of medical AI startup MD.ai, and radiologist Luke Oakden-Rayner, to train two algorithms and understand how it matches with a medical professional as it learns. One detects the presence of tumorous nodules, and the second gauges the potential of it being malignant.

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