There has been quite a bit of hype over the last several years about how artificial intelligence (AI) would transform health care. Translating the predictive power of AI algorithms into research methods and clinical practice, however, has proved challenging, which inevitably leads to disillusionment. But rather than getting frustrated with AI and machine learning, I would argue that strategic and ethical deployment of artificial intelligence will, by necessity, be central to the success of precision health research over the next decade.
Several factors are coming together to make AI more critical to progress. One is that the sheer volume of data being generated by electronic health records, medical device data, genomics, biospecimens, imaging and digital health apps has expanded far beyond human capabilities to analyze it. Because the amount of data and the number of data sources has exploded, it’s becoming very difficult to derive further value based on standard methods of analysis.
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