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Table 3 P value matrix of various model performances (AUROC) for in-hospital mortality prediction. U, T, S represents unstructured data, temporal signals, and static information respectively

From: Combining structured and unstructured data for predictive models: a deep learning approach

  LR RF Fusion-CNN Fusion-LSTM
T + S U U + T + S T + S U U + T + S T + S U U + T + S T + S U U + T + S
LR \(T + S\) 1 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
U < 0.001 1 < 0.001 < 0.001 < 0.001 < 0.001 0.5644 0.7432 < 0.001 0.0047 0.3918 < 0.001
\(U + T + S\) < 0.001 < 0.001 1 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.0018 < 0.001 < 0.001 < 0.001
RF \(T + S\) < 0.001 < 0.001 < 0.001 1 < 0.001 1 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
U < 0.001 < 0.001 < 0.001 < 0.001 1 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
\(U + T + S\) < 0.001 < 0.001 < 0.001 1 < 0.001 1 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
Fusion-CNN \(T + S\) < 0.001 0.5644 < 0.001 < 0.001 < 0.001 < 0.001 1 0.5428 < 0.001 < 0.001 0.6591 < 0.001
U < 0.001 0.7432 < 0.001 < 0.001 < 0.001 < 0.001 0.5428 1 < 0.001 < 0.001 0.232 < 0.001
\(U + T + S\) < 0.001 < 0.001 0.0018 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 1 < 0.001 < 0.001 0.6062
Fusion-LSTM \(T + S\) < 0.001 0.0047 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 1 0.0011 < 0.001
U < 0.001 0.3918 < 0.001 < 0.001 < 0.001 < 0.001 0.6591 0.232 < 0.001 0.0011 1 < 0.001
\(U + T + S\) < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.6062 < 0.001 < 0.001 1