Avive Solutions’ AED Machine Learning Algorithm Exceeds American Heart ... the convolution neural network demonstrated greater than 99% diagnostic accuracy for shockable and non-shockable rhythms.

They've developed an algorithm that can detect 14 types of arrhythmia -- they also claim that based on their tests, ... and a lot of people with abnormal heart rhythms don't even show symptoms.

The cardiac arrest treatment algorithm divides cardiopulmonary resuscitation into the treatment of shockable rhythms – ventricular fibrillation (VF) and pulseless ventricular tachycardia (VT) (Figure ...

Once activated, the novel algorithm tracks a user’s pulse rate during periods of inactivity. Possible atrial fibrillation is noted after at least 30 minutes of irregular heart rhythms.

Alongside the FDA's 510(k) clearance, RHYTHM AI has also reported the first uses of the new version of the technology to treat AFib patients – at Baptist Health in Jacksonville, Florida – with ...

Heart rhythms associated with cardiac arrest are divided into two groups: shockable rhythms (VF or pVT) and non-shockable rhythms (asystole and pulseless electrical activity or PEA).

However, non-shockable patients treated with AAM showed better outcomes." A shockable rhythm indicates receptivity to defibrillation, while a non-shockable rhythm is treated with only CPR, often ...

Is Hypothermia After Cardiac Arrest Effective in Both Shockable and Nonshockable Patients? Insights From a Large Registry. Dumas F, Grimaldi D, Zuber B, et al. Circulation. 2011; 123:877-886. A ...