Tuberculosis kills 1.4 million people every year, primarily in places where poverty and deprivation conspire to make people uniquely vulnerable, and unable to get lifesaving care in time.
Google is now joining a global fight to snuff out the disease, using AI to automate its detection — and expedite treatment — in communities where physicians are in short supply. A new study published Tuesday in Radiology, the journal of the Radiological Society of North America, found that its AI model performed as well as radiologists at detecting tuberculosis on chest X-rays.
Google is not the first to develop an AI system to detect TB, nor is its tool likely to make a dent in death rates anytime soon. But outside experts said its early results are especially promising given their consistency across diverse populations of patients. The model met or exceeded performance standards set by the World Health Organization when tested on historical patient data drawn from China, India, the United States, and Zambia.
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