Predicting the clinical trajectory of individual patients with implantable cardioverter-defibrillators (ICDs) is essential to inform clinical care. Machine learning approaches can potentially overcome the limitations of conventional statistical methods and provide more accurate, personalized risk estimates.

中文翻译：

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基于机器学习的植入式心律转复除颤器患者死亡和住院预测


预测植入式心律转复除颤器 （ICD） 个体患者的临床轨迹对于为临床护理提供信息至关重要。机器学习方法有可能克服传统统计方法的局限性，并提供更准确、个性化的风险估计。