Envisioning Cardiac Electrophysiology with Artificial Intelligence

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Cardiac arrhythmias are a major global healthcare problem and there is significant scope for improving their diagnosis and treatment. The EP mapping system, combined with an ablation system, has great potential for improvement by using modern machine learning techniques. These intelligent clinical decision support systems with appropriate machine learning techniques, offer a powerful approach towards personalized care by improving effectiveness and accuracy of EP procedures.

With the aging population contributing to rising cases of cardiac arrhythmias like atrial fibrillation (AF), we see strong growth in the electrophysiology (EP) cardiac mapping system device market, being the primary treatment of choice for AF. Considering that AF ablation is a complicated procedure requiring extensive skills of electrophysiologists, the EP mapping system has great potential for improvement by integrating modern machine learning techniques.

With healthcare providers looking for a holistic solution, cardiac EP systems have evolved into diagnostic and therapeutic systems with radiofrequency ablation (RFA) to treat the arrhythmia foci. As technology advances, various industries are adopting technologies such as digital transformation, internet of things (IoT), artificial intelligence (AI), nanotechnology, and so on within their product/service portfolio and the medical device industry is no exception.

Read our point of view for more insights on software-based solutions incorporating AI within EP systems that can improve overall system performance, improve the therapeutic outcomes, reduce procedural time, and assist the electrophysiologist during the procedure.

Envisioning Cardiac Electrophysiology...

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Rajashree Damle

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