November 30, 2016 (LocalOrg) - MIT Technology Review recently published an article titled, "An AI Ophthalmologist Shows How Machine Learning May Transform Medicine." In it, it describes how Google researchers at their DeepMind subsidiary used artificial intelligence (AI) to scan images of human eyes to detect a common form of blindness as well as, or better than trained experts can.
They achieved this by using the same machine learning techniques Google and other tech giants including Facebook use to analyze images that show up on their web platforms. Instead of creating complex programs to handle every conceivable detail in an image, researchers instead teach machines how to learn on their own when exposed to large volumes of pre-tagged examples.
In the MIT Technology Review article, DeepMind's algorithm studied some 128,000 retinal images that were already classified by ophthalmologists.
The breakthrough is only the latest in a long line of advances in AI. AI machine learning is already being widely used in real-world applications, including sifting through the United Kingdom's National Health Service's records, automatically tagging - and flagging - images, videos, and voice across vast social networks, improving efficiency at utility plants by spotting trends and automatically adjusting power consumption, inputs, and outputs, as well as developing protocols for both pharmaceutical production and genetic engineering.
DeepMind's research into analyzing medical imagery is already set to be integrated into its UK NHS collaboration, according to the Guardian in an article titled, "Google DeepMind pairs with NHS to use machine learning to fight blindness," which reports:
They achieved this by using the same machine learning techniques Google and other tech giants including Facebook use to analyze images that show up on their web platforms. Instead of creating complex programs to handle every conceivable detail in an image, researchers instead teach machines how to learn on their own when exposed to large volumes of pre-tagged examples.
In the MIT Technology Review article, DeepMind's algorithm studied some 128,000 retinal images that were already classified by ophthalmologists.
The breakthrough is only the latest in a long line of advances in AI. AI machine learning is already being widely used in real-world applications, including sifting through the United Kingdom's National Health Service's records, automatically tagging - and flagging - images, videos, and voice across vast social networks, improving efficiency at utility plants by spotting trends and automatically adjusting power consumption, inputs, and outputs, as well as developing protocols for both pharmaceutical production and genetic engineering.
DeepMind's research into analyzing medical imagery is already set to be integrated into its UK NHS collaboration, according to the Guardian in an article titled, "Google DeepMind pairs with NHS to use machine learning to fight blindness," which reports:
Google DeepMind has announced its second collaboration with the NHS, working with Moorfields Eye Hospital in east London to build a machine learning system which will eventually be able to recognise sight-threatening conditions from just a digital scan of the eye.In essence, those who control AI technology have access to algorithms that can perform specific tasks better than any trained human can. This confers on those who control this technology an immense advantage and creates disparity those without AI technology have no means of competing against.
The collaboration is the second between the NHS and DeepMind, which is the artificial intelligence research arm of Google, but Deepmind’s co-founder, Mustafa Suleyman, says this is the first time the company is embarking purely on medical research. An earlier, ongoing, collaboration, with the Royal Free hospital in north London, is focused on direct patient care, using a smartphone app called Streams to monitor kidney function of patients.
