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Table 2 Multilayer perceptron models predicting 45-year all-cause mortality (1447 deaths among 1591 men) by two methods

From: Artificial neural networks versus proportional hazards Cox models to predict 45-year all-cause mortality in the Italian Rural Areas of the Seven Countries Study

Rank Gini Variable Keep
NEURAL NETWORK FORCED
1 0.15950 Age (AGE0: years) 1
2 0.60615 Cigarettes smoked per day (CIG0: N) 1
3 0.64475 Family history of CVD(famcv0: codes 0–1) 1
4 0.64790 Mean blood pressure (MBP: mmHg) 1
5 0.65872 Serum cholesterol (CHOL0: mmol/l) 1
6 0.67052 Corneal arcus (gero0: codes 0–1) 1
7 0.67484 Mother status (Mother0: codes 0–1) 1
8 0.67680 Prevalence DIAB (pdiab0: codes 0–1) 1
9 0.68081 Forced expiratory volume (fev0trans0: l/m2) 1
10 0.68321 Heart rate (hr0: beats/min) 1
11 0.68362 Father status (Father0: codes 0–1) 1
12 0.68414 Body mass index (BMI0: Kg/m2) 1
13 0.68516 Minor ECG abnormalities (MinorECG0: codes 0–1) 1
14 0.68524 Prevalence CVD (Pcvd0: codes 0–1) 1
15 0.68579 Arm circumference (midclean0: cm) 1
16 0.68664 Body mass index2 (BMIsq0) [(Kg/m2)2] 1
17 0.68813 Prevalence cancer (pcan0: codes 0–1) 0
18 0.68872 Physical activity (PHYAC0: codes 1-2-3) 0
NEURAL NETWORK STEPWISE
1 0.17824 Age (years) 1
2 0.60661 Cigarettes smoked per day (N) 1
3 0.65370 Mean blood pressure (mmHg) 1
4 0.67844 Mother status (codes 0–1) 1
5 0.67918 Corneal arcus (codes 0–1) 1
6 0.68104 Heart rate (beats/min) 1
7 0.68347 Father status (codes 0–1) 1
8 0.68468 Minor ECG abnormalities (codes 0–1) 1
9 0.69231 Physical activity (codes 1-2-3) 1
10 0.69329 Family history (codes 0–1) 1
11 0.69480 Prevalence DIAB (codes 0–1) 1
12 0.69603 Serum cholesterol (mmol/l) 1
13 0.69854 Prevalence CVD (codes 0–1) 1
  1. Gini = (ROC-0.5)*2 [see text for further details]; Keep = 1: the variable may stay in the model; Keep = 0: removing the variable improves the training set model.
  2. CVD = cardiovascular disease; DIAB = diabetes. Variables’ codes are included in parentheses to interpret the Figure in Additional file 1: Appendix 2.