Google's DeepMind to use AI in diagnosing eye disease

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The artificial intelligence software is learning how to recognize early signs of two eye diseases.Video provided by Newsy Newslook A scan of a human eye. SAN FRANCISCO -- Google plans to use more than one million anonymized eye scans to teach computers how to diagnose ocular disease. The Menlo Park, Calif.-based company has signed a deal with a British eye hospital to use artificial intelligence to learn from the medical records of 1.6 million patients in London hospitals. The goal is to teach a computer program to recognize the signs of two common types of eye disease, diabetic retinopathy and age-related macular degeneration. That's something humans are surprisingly imperfect at.


Google's DeepMind to use AI in diagnosing eye disease

USATODAY - Tech Top Stories

A scan of a human eye. SAN FRANCISCO -- Google plans to use more than one million anonymized eye scans to teach computers how to diagnose ocular disease. The Menlo Park, Calif.-based company has signed a deal with a British eye hospital to use artificial intelligence to learn from the medical records of 1.6 million patients in London hospitals. The goal is to teach a computer program to recognize the signs of two common types of eye disease, diabetic retinopathy and age-related macular degeneration. That's something humans are surprisingly imperfect at.


Artificial intelligence could build new drugs faster than any human team

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Artificial intelligence algorithms are being taught to generate art, human voices, and even fiction stories all on their own--why not give them a shot at building new ways to treat disease? Atomwise, a San Francisco-based startup and Y Combinator alum, has built a system it calls AtomNet (pdf), which attempts to generate potential drugs for diseases like Ebola and multiple sclerosis. The company has invited academic and non-profit researchers from around the country to detail which diseases they're trying to generate treatments for, so AtomNet can take a shot. The academic labs will receive 72 different drugs that the neural network has found to have the highest probability of interacting with the disease, based on the molecular data it's seen. Atomwise's system only generates potential drugs--the compounds created by the neural network aren't guaranteed to be safe, and need to go through the same drug trials and safety checks as anything else on the market.


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Artificial intelligence algorithms are being taught to generate art, human voices, and even fiction stories all on their own--why not give them a shot at building new ways to treat disease? Atomwise, a San Francisco-based startup and Y Combinator alum, has built a system it calls AtomNet (pdf), which attempts to generate potential drugs for diseases like Ebola and multiple sclerosis. The company has invited academic and non-profit researchers from around the country to detail which diseases they're trying to generate treatments for, so AtomNet can take a shot. The academic labs will receive 72 different drugs that the neural network has found to have the highest probability of interacting with the disease, based on the molecular data it's seen. Atomwise's system only generates potential drugs--the compounds created by the neural network aren't guaranteed to be safe, and need to go through the same drug trials and safety checks as anything else on the market.


Large Companies Eye Collaboration as Entry into AI

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Edwards Lifesciences is delving deeper into the realm of artificial intelligence through a partnership with San Francisco-based Bay Labs. The goal of the collaboration, which has multiple initiatives is to improve the detection of heart disease. Some of the initiatives include, the development of new AI-powered algorithms in Bay Labs' EchoMD measurement and interpretation software suite; support for ongoing clinical studies at institutions; and the integration of EchoMD algorithms into Edwards Lifesciences' CardioCare quality care navigation platform. Irvine, CA-based Edwards' CardioCare program combines clinical consulting expertise with a cloud-based platform to facilitate in the identification, referral, and care pathway management of patients with structural heart disease. CardioCare can help hospitals improve quality by reducing variability in echocardiography and ensure effective communication between care settings to ensure patients access to care.