Despite all the rage among startups, Silicon Valley and health IT professionals about how artificial intelligence (AI) could revolutionize healthcare, the technology just isn’t there yet, according to a report in VentureBeat.
What’s holding AI back for now isn’t money, considering tech giants such as IBM and Apple are investing billions in the technology. Applications still need to achieve artificial narrow intelligence, or ANI, or outperforming humans in fairly complex scenarios.
“To date, the sweet spot in healthcare AI has been pairing algorithms with structured exercises in reading patient data and medical images to train machines to detect abnormalities. This training is called ‘deep learning,'” healthcare consultant Brian Scogland said. “In the same way, algorithms are being used to sift through vast amounts of medical literature to inform treatment decisions where it would be too onerous a task to have a human read through the same journals.”
There are still technological, psychological and regulatory barriers to overcome, however, which makes predicting when the big breakthrough will occur difficult.
“I have no doubt that sophisticated learning and AI algorithms will find a place in health care over the coming years,” said Andy Schuetz, a senior data scientist at Sutter Health. “I don’t know if it’s two years or 10—but it’s coming.”
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