The automatic, unsupervised analysis of biomedical time series is vital for diagnostic and preventive medicine, enabling fast and reliable data processing that reveals clinical insights without human intervention. This article explores and quantifies the benefits of modern deeplearning architectures of varying degrees of complexity.

中文翻译：

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关于深度表示学习的有效性：心房颤动案例

生物医学时间序列的自动、无监督分析对于诊断和预防医学至关重要，可实现快速可靠的数据处理，无需人工干预即可揭示临床见解。本文探讨并量化了不同复杂程度的现代深度学习架构的好处。