The world knows no deadlier assassin than heart disease. It accounts for one in four fatalities in the US. Early detection remains the key to saving lives, but catching problems at the right time too often relies upon dumb luck. The most effective way of identifying problems involves an EKG machine, a bulky device with electrodes and wires.
Most people visit a doctor for an electrocardiogram. That, too, is no guarantee, because the best detection means being tested when a potential problem reveals itself. Otherwise, early signs of heart disease might go undetected.
At-risk patients might find a compact, easy to use EKG machine a good option. Like so many other gadgets, portable EKG machines are getting ever smaller—just look at products like Zio, HeartCheck, and QuardioCore.
The Kardia from AliveCor is about the width of two sticks of gum. Stick the $100 device on the back of your phone or slip it into your wallet, place a few fingers on it for 30 seconds, and you’ve got a medical-grade EKG reading on your phone.
But the bigger story is not in the gadget’s size, but in what happens with the heart data it collects. The company uses neural networks and algorithms to identify signs of heart disease, an approach it hopes might change how cardiologists diagnose patients.
The company was successful at convincing FDA, MayoClinic and the investors that devices’ ease of use will lead to more frequent testing and increase the likelihood of early detection. About a month of use builds a heart profile and then Kardia’s data-driven algorithm can detect if something goes amiss. Your doctor receives a message only when the anomaly is detected.
Why it is hot: Future of diagnostics is in data-driven approach. With IBM Watson and other innovations in machine learning, we are up for a healthier future!!!