Researchers at the University of Washington have developed a new machine-learning system, called Prescience, which uses input from patient charts and standard operating room sensors to predict the likelihood that a patient will develop hypoxemia -- a condition when blood oxygen levels dip slightly below normal. Hypoxemia can lead to serious consequences, such as infections and abnormal heart behavior. During surgery, anesthesiologists monitor and manage patients to make sure they are safe and breathing well. But these doctors can't always predict when complications will arise. Prescience provides real-world explanations behind its predictions. With this information, anesthesiologists can better understand why a patient is at risk for hypoxemia and prevent it before it happens. The research team estimates that Prescience could improve the ability of anesthesiologists to anticipate and prevent 2.4 million more hypoxemia cases in the United States every year.
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