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Table 8 Optimal feature vectors selected by different models from bootstrap test data

From: A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery – Part II: an illustrative example

No.

BL

BQ

k NN

LR

HS

DS

ANN1

ANN2

1

O2ER

O2ER

Post-CI

O2ER

O2ER

SvO2

O2ER

O2ER

2

VCO2

DO2

O2ER

VCO2

VCO2

Card-ID

Card-ID

VO2

3

Card-ID

Card-ID

Card-ID

Card-ID

Card-ID

DO2

VO2

Card-ID

4

PVD

 

PVD

PVD

PVD

O2ER

PVD

PVD

5

TBU

 

TBU

TBU

TBU

EM

TBU

Gly

6

EM

  

EM

EM

BSA

Pre-CI

Gender

7

SAP

  

SAP

SAP

AD

EM

MVR

8

SaO2

  

Pre-CI

Pre-CI

CHF

WBC

Cr

9

   

WBC

WBC

MVR

Age

AVO2

10

   

SaO2

SaO2

MR

SaO2

Arrhy

11

   

PvO2

PvO2

PVD

AD

 

12

   

AD

AD

Diab

P/F

 

13

   

PaO2

PaO2

VCO2

PVS

 

14

   

Cr

Cr

CABG-C

  

15

     

PAH

  

16

     

IABP

  
  1. BL, Bayes linear model; BQ, Bayes quadratic model; k NN, k-nearest neighbour model; LR, logistic regression model; HS, Higgins score system; DS, direct score system; ANN1, one-layer artificial neural network; ANN2, two-layer artificial neural network. Predictor variable abbreviations are indicated in Tables 1-6.
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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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