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基于连词(Copula)的深度学习模型在处理竞争性风险中的应用
本研究提出结合可学习Copula函数(Clayton、Frank、Gaussian)与CNN、LSTM及CNN-LSTM深度学习模型的方法,用于竞争风险生存分析。通过模拟数据和真实临床数据验证,发现Clayton和Frank Copula模型在Brier score、准确率和宏F1分数上表现最优,尤其Clayton LSTM模型在模拟数据中 ...
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