Cardiac arrhythmias are a major risk factor for sudden cardiac death, which accounts for 15% to 20% of all deaths worldwide. Causes for arrhythmias are diverse and include genetic factors, patients’ physical and mental condition, and certain medication. Onset and severity of arrhythmic events in patients are notoriously unpredictable, particularly in younger and patients with no history of cardiac disease. To address this issue, Boon-Seng Soh, Jeremy Kah Sheng Pang and colleagues from Institute of Molecular and Cell Biology, Singapore combined stem cell technology with machine learning, which enabled them to predict with a high degree of accuracy arrhythmias in the lab. The results of the research were recently published in the journal Stem Cell Reports.
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