What if AI could predict more accurately than doctors who would have a heart attack, and possibly, when? This is now happening through 4 computers learning algorithms and those are now beating the International guidelines for estimating a patient's risk level.
Where do we take it from here? No more needs for a doctor's visit, only being connected to your wearables which would be constantly updated with the latest data tracked straight from your body.
Less false alarms, faster response times, and in case of emergency (heart beat slowing down) having an ambulance called straight to where you are. Think of how many lives we could save with this!
That's pretty accurate but Stephen Weng and his team set about to make it better. They built four computer learning algorithms, then fed them data from 378,256 patients in the United Kingdom. The systems first used around 295,000 records to generate their internal predictive models. Then they used the remaining records to test and refine them. The algorithms results significantly outperformed the AAA/AHA guidelines, ranging from 74.5 to 76.4 percent accuracy. The neural network algorithm tested highest, beating the existing guidelines by 7.6 percent while raising 1.6 percent fewer false alarms.