Skip to main content

Table 7 P value matrix of various model performances (AUROC) for 30-day readmission 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 0.0208 < 0.001 < 0.001 0.0158 0.0076 < 0.001
U < 0.001 1 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.2449 < 0.001
\(U + T + S\) < 0.001 < 0.001 1 < 0.001 < 0.001 < 0.001 0.3156 0.0954 < 0.001 < 0.001 < 0.001 < 0.001
RF \(T + S\) < 0.001 < 0.001 < 0.001 1 0.073 0.116 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
U < 0.001 < 0.001 < 0.001 0.073 1 0.7452 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
\(U + T + S\) < 0.001 < 0.001 < 0.001 0.116 0.7452 1 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
Fusion-CNN \(T + S\) 0.0208 < 0.001 0.3156 < 0.001 < 0.001 < 0.001 1 0.0661 0.0011 0.1757 0.0012 < 0.001
U < 0.001 < 0.001 0.0954 < 0.001 < 0.001 < 0.001 0.0661 1 0.0011 < 0.001 < 0.001 < 0.001
\(U + T + S\) < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.0011 0.0011 1 < 0.001 < 0.001 0.07
Fusion-LSTM \(T + S\) 0.0158 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.1757 < 0.001 < 0.001 1 < 0.001 < 0.001
U 0.0076 0.2449 < 0.001 < 0.001 < 0.001 < 0.001 0.0012 < 0.001 < 0.001 < 0.001 1 < 0.001
\(U + T + S\) < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.07 < 0.001 < 0.001 1