Question: Is there a cloud-based solution that uses AI to improve arrhythmia diagnostics and reduce analysis time?

If you're looking for a cloud-based system that uses AI to help diagnose arrhythmia and speed up analysis, Cardiologs is a good choice. The system uses deep-learning technology trained on more than 20 million recordings to increase specificity and sensitivity and automate much of the manual work that's needed to make an expert-level ECG diagnosis. By cutting analysis time by up to 78%, [Cardiologs] helps healthcare providers manage cardiac care better, with features like customizable reports and data sharing.

Another good choice is Philips Mobile Cardiac Telemetry (MCOT). The system offers near real-time arrhythmia analysis with high accuracy, thanks to the SmartDetectAI algorithm. It detects atrial fibrillation with 100% sensitivity and 100% positive predictivity. With flexible wear options and a telehealth interface, MCOT can support clinical pathways for a range of cardiac conditions, making it a good choice for health care providers trying to proactively manage patient populations.

If you're looking for something more focused, check out Eko. Eko offers digital stethoscopes that use AI analysis to help detect cardiovascular disease. The company's platform includes features like AI-based detection of murmurs and atrial fibrillation, and it integrates with telehealth systems for remote patient care. That makes Eko a good choice for health care providers trying to use AI for more accurate diagnoses and better workflow.