Screening for Hypertension and Sleep Apnea with DeepHeart

When we talk about artificial intelligence in medicine, we often debate whether machines will replace tasks doctors do today. A more tantalizing possibility is performing tasks doctors can't--using large data sets, and modern computational tools like deep learning, to recognize patterns too subtle for any human to discern. Today, we're presenting early clinical results showing Cardiogram's deep neural network, DeepHeart, can do just that: recognize hypertension and sleep apnea from wearable heart rate sensors with 82% and 90% accuracy, respectively [1]. The American Heart Association is highlighting this work, conducted in partnership with the UC San Francisco's Health eHeart Study, as one of three Best Abstracts in Health Tech at their annual AHA Scientific Sessions, a meeting of roughly 18,000 cardiologists. Globally, 1.1 billion people have hypertension (chronic high blood pressure) and 1 in 5 are undiagnosed.