Artificial intelligence is a perception around which the overall technology and processes are evolving. It has been now deep rooted in many of our daily operations and applications, and some of them are so deep that we ourself cannot carry out the work without its functionality. One of the most common examples of the AI is the speech recognition, which is integrated with every smart device nowadays. The magic of this technology doesn’t end here as its efficiency is bound to make some superior alterations in the process, no matter in what section or application it is applied.
Emphasizing on its current trends, the artificial intelligence is now entering the medical and wellness industry rapidly. Stanford scientist has created an AI system that can identify irregular heartbeats can be life-threatening by swiftly penetrating the heart rhythm data.
The group of algorithm delivers efficient results compared to expert cardiologists and have opened the way to monitor the data sitting at the remote locations, where the facility of cardiology is hard to find. The system can
rapidly fetch the precise diagnoses of heart arrhythmias without taking the people to cardiologists.
A graduate student at Stanford University in the US, Awni Hannun, said, “The best part about the technology isn’t the diagnoses of the abnormality, to do it with great precision with a large number of variable abnormalities is unique.”
People detected with cardiac arrest get an electrocardiogram (ECG) at the doctor’s place. If incase the ECG doesn’t show the problem, the doctor then recommends patient a wearable ECG that can examine the heartbeats continuously for certain weeks. Later, after the derived duration of monitoring that involves hundreds of hours approximately, a consolidated data is inspected second-by-second to check if there is any indication of arrhythmias. In this process, some of the heartbeats are extremely difficult to distinguish from risk-free heartbeat irregularities.
Wherein, the research led by Andrew Ng is developed in such a way that with its deep learning algorithm, 13 types of arrhythmia are extracted from an ECG signals. It is believed by the researchers that this algorithm will make the arrhythmia diagnoses and treatment more accessible for the patient who cannot visit the cardiologists personally.
Around the globe, in many parts of the world, there are some regions that witness the scarcity of basic medical facilities. This AI-based algorithm can be a tool for expert-level arrhythmia diagnosis for people who live in rural areas where the medical services are hard to obtain.