RESEARCH
GOOGLE'S DEEP DIVE INTO HEALTHCARE USING AI By
Chloe Palumbo Esther Beck
Alan Turing’s 1950 paper, Computer Machinery and Intelligence, introduced a simple yet novel question: Can machines think? His answer came in the form of the Turing Test, which sought to determine whether a computer could reliably pass as a human when prompted with a series of questions. Turing’s work set the precedent for artificial intelligence by bringing the question of whether machines can exhibit human intelligence to the fore. But what exactly is artificial intelligence? For many, the term “artificial intelligence” conjures up images of machines taking over the world in some sci-fi apocalypse. Despite all the buzz about artificial intelligence in the past decade, most people still only have a vague understanding of what exactly artificial intelligence is and the role it plays in modern society. At the most rudimentary level, artificial intelligence is the act of replicating human intelligence in computer systems. Whether it be through speech-recognition or decision making, artificial intelligence has made profound leaps in industries as wide-ranging as automobiles and healthcare. One such advance came in 2008 after Google launched their Google Health project, marking the commencement of their venture into the healthcare industry. Originally designed to allow Google users to centralize their health records, the Google Health project has shifted its focus in recent years to artificial
intelligence research. One predominant focus of the Google Health project is Acute Kidney Injury (AKI) prevention. At a staggering 13.3 million cases worldwide per year, AKIs pose a significant global health threat by causing kidney failure in as less as two days due to the accumulation of waste products in the blood. If diagnosed early enough, experts believe that up to 30% of AKIs are treatable, but early detection systems have plenty of room for improvement. The DeepMind team at Google Health seized this opportunity to initiate a research project that employs artificial intelligence in order to predict AKIs as quickly as 48 hours before they strike. To do this, they’re testing a neural network that processes electronic health records at certain time steps and outputs the probability of AKI development within the next 48 hours. Any probability above a certain threshold indicates a positive result and will notify clinicians as soon as possible. Additionally, the model provides a measure of uncertainty with each prediction that allows clinicians to distinguish between more and less ambiguous cases. The artificial intelligence technology is so accurate, in fact, that it correctly detected AKI in 90% of patients with conditions that became so severe they required dialysis. In addition to acute kidney injuries, Google Health’s artificial intelligence technology has ventured
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