Atrial fibrillation, also known as atrial fibrillation, is the most common persistent arrhythmia. However, as people age, the incidence of atrial fibrillation will continue to increase. One of the greatest hazards of atrial fibrillation is stroke. This type of acute cerebrovascular disease can cause death when it is severe. In general, catheter radiofrequency ablation is considered as one of the methods for treating arrhythmia. But since the 1990s, the success rate of this method has been disappointing.
Marcos McGill-Leigher and his colleagues at Imperial College in London published an article in the “Open Science of the Royal Society†that they applied machine learning algorithms to medical treatment and demonstrated how to use artificial intelligence methods. The source of atrial fibrillation is accurately located in a simple model, and only the electrocardiography available in the clinical environment is used. The researchers said that the current stage of the work is only a preliminary demonstration. There are still many problems in policy, technology, and ethics that need to be broken in the future. However, it proposes a possible approach and has the potential to improve the long-term treatment plan for this disease.
(Source of this column: Royal Society's official website: Reporter Zhang Mengran)
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