From: Deep-learning model for screening sepsis using electrocardiography
Rank | Logistic regression (deviance difference) | Random forest (mean decrease Gini) | Deep learning (relative importance) |
---|---|---|---|
1 | QTc (492) | Heart rate (473.2) | QTc (0.193) |
2 | Age (274) | T-wave axis (472.1) | QT interval (0.168) |
3 | QRS duration (207) | R-wave axis (443.2) | PR interval (0.121) |
4 | T-wave axis (145 | QTc (429.5) | T-wave axis (0.085) |
5 | QT interval (101) | P-wave axis (413.3) | QRS duration (0.082) |
6 | Heart rate (63) | Age (394.5) | Age (0.079) |
7 | P-wave axis (18) | QRS duration (386.2) | Heart rate (0.078) |
8 | R-wave axis (11) | QT interval (367.0) | P-wave axis (0.075) |
9 | PR interval (2) | PR interval (363.0) | R-wave axis (0.063) |
10 | Sex (− 1) | Sex (0.1) | Sex (0.055) |