基于模式识别和集成CNN-LSTM的阵发性房颤预测模型

杨萍,王丹,康子健,李童,付利华,余悦任

Prediction model of paroxysmal atrial fibrillation based on pattern recognition and ensemble CNN-LSTM

Ping YANG,Dan WANG,Zi-jian KAGN,Tong LI,Li-hua FU,Yue-ren YU

表 1 模式匹配长度为2时，序列S的模式转移频次和转移概率

Tab.1 Pattern transition frequencies and probabilities with pattern matching length of sequence of 2

模式 PTF2 PTP2 a b c 总计 a b c aa 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ab 0.0 0.0 1.0 1.0 0.0 0.0 1.0 ac 0.0 1.0 1.0 2.0 0.0 0.5 0.5 ba 0.0 0.0 2.0 2.0 0.0 0.0 1.0 bb 0.0 0.0 0.0 0.0 0.0 0.0 0.0 bc 0.0 0.0 1.0 1.0 0.0 0.0 1.0 ca 0.0 0.0 0.0 0.0 0.0 0.0 0.0 cb 2.0 0.0 0.0 2.0 1.0 0.0 0.0 cc 0.0 1.0 0.0 1.0 0.0 1.0 0.0