Hospital mortality prediction in traumatic injuries patients: comparing different SMOTE-based machine learning algorithms

Hassanzadeh, Roghayyeh; Farhadian, Maryam; Rafieemehr, Hassan

doi:10.1186/s12874-023-01920-w

Table 3 Comparison of the prediction performances of SMOTE-based machine learning methods on the test dataset

From: Hospital mortality prediction in traumatic injuries patients: comparing different SMOTE-based machine learning algorithms

Methods	Dataset	Sensitivity	Specificity	PPV	NPV	Accuracy	AUC	G-means	F1-Score	McNemar
		Mean (SE)	Mean (SE)	Mean (SE)	Mean (SE)	Mean (SE)	Mean (SE)	Mean (SE)	Mean (SE)	Mean (SE)
SVM	Original	0.55(0.0469)	1(0)	1(0)	0.96(0.0034)	0.97(0.0037)	0.72(0.0095)	0.66(0.0150)	0.60(0.0192)	0.75(0.0165)
	SMOTE	0.98(0.0009)	0.97(0.0018)	0.97(0.0018)	0.99(0.0001)	0.99(0.0011)	0.98(0.0009)	0.98(0.0009)	0.98(0.0009)	0.26(0.0251)
	B-SMOTE1	0.99(0.0011)	0.96(0.0019)	0.96(0.0019)	0.99(0.0014)	0.98(0.0011)	0.98(0.0011)	0.98(0.0011)	0.98(0.0011)	0.74(0.0098)
	B-SMOTE2	0.95(0.0035)	0.96(0.0029)	0.96(0.0030)	0.95(0.0037)	0.95(0.0020)	0.95(0.0019)	0.95(0.0020)	0.95(0.0019)	0.53(0.0322)
	SMOTE-NC	0.98(0.0004)	0.99(0.0001)	0.99(0.0001)	0.98(0.0005)	0.99(0.0004)	0.99(0.0002)	0.99(0.0002)	0.99(0.0002)	0.33(0.0096)
	SVM-SMOTE	0.99(0.0012)	0.96(0.0024)	0.94(0.0040)	0.99(0.0010)	0.98(0.0015)	0.98(0.0012)	0.98(0.0012)	0.97(0.0021)	0.73(0.0122)
ANN	Original	0.78(0.7474)	1(0)	0.76(0.0203)	0.97(0.0051)	0.98(0.0217)	0.89(0.1182)	0.81(0.0223)	0.69(0.0246)	0.26(0.816)
	SMOTE	1(0)	1(0)	1(0)	1(0)	1(0)	1(0)	1(0)	1(0)	NA
	B-SMOTE1	1(0)	1(0)	1(0)	1(0)	1(0)	1(0)	1(0)	1(0)	NA
	B-SMOTE2	0.98(0.0014)	0.98(0.0018)	0.98(0.0018)	0.98(0.0013)	0.99(0.0016)	0.98(0.0012)	0.98(0.0012)	0.98(0.0013)	0.21(0.0249)
	SMOTE-NC	0.97(0.0016)	0.98(0.0012)	0.98(0.0013)	0.98(0.0015)	0.99(0.0015)	0.98(0.0012)	0.98(0.0012)	0.98(0.0013)	0.20(0.0232)
	SVM-SMOTE	0.98(0.0003)	0.99(0.0002)	0.98(0.0003)	0.99(0.0001)	0.99(0.0002)	0.98(0.0001)	0.98(0.0001)	0.98(0.0003)	0.33(0.0031)
NB	Original	0.51(0.0491)	0.95(0.0048)	0.42(0.0324)	0.96(0.0037)	0.91(0.0064)	0.70(0.0241)	0.66(0.0170)	0.44(0.0190)	0.53(0.0337)
	SMOTE	0.99(0.0004)	0.91(0.0052)	0.92(0.0046)	0.99(0.0005)	0.95(0.0026)	0.95(0.0026)	0.95(0.0028)	0.96(0.0025)	0.87(0.0148)
	B-SMOTE1	0.99(0.0012)	0.92(0.0046)	0.93(0.0042)	0.99(0.0016)	0.96(0.0024)	0.96(0.0023)	0.96(0.0024)	0.96(0.0023)	0.85(0.0111)
	B-SMOTE2	0.96(0.0036)	0.86(0.0059)	0.87(0.0055)	0.96(0.0040)	0.91(0.0035)	0.91(0.0034)	0.91(0.0035)	0.91(0.0034)	0.75(0.0293)
	SMOTE-NC	0.98(0.0019)	0.95(0.0032)	0.95(0.0032)	0.98(0.0020)	0.96(0.0018)	0.96(0.0018)	0.96(0.0019)	0.96(0.0019)	0.61(0.0282)
	SVM-SMOTE	0.99(0.0012)	0.91(0.0050)	0.88(0.0063)	0.99(0.0079)	0.94(0.0031)	0.95(0.0025)	0.95(0.0028)	0.93(0.0036)	0.86(0.0129)
RF	Original	0.53(0.0348)	0.99(0.0005)	0.98(0.0222)	0.95(0.0041)	0.96(0.0039)	0.71(0.0122)	0.65(0.0176)	0.60(0.0224)	0.76(0.0230)
	SMOTE	0.99(0.0003)	0.99(0.0001)	0.99(0.0001)	0.99(0.0003)	0.99(0.0003)	0.99(0.0001)	0.99(0.0001)	0.99(0.0002)	0.07(0.0062)
	B-SMOTE1	0.98(0.0007)	0.99(0.0002)	0.99(0.0002)	0.98(0.0010)	0.99(0.0005)	0.98(0.0003)	0.99(0.0004)	0.99(0.0003)	0.08(0.0109)
	B-SMOTE2	0.97(0.0025)	0.98(0.0021)	0.97(0.0023)	0.97(0.0025)	0.98(0.0019)	0.97(0.0015)	0.97(0.0015)	0.97(0.0016)	0.38(0.0293)
	SMOTE-NC	0.97(0.0017)	0.98(0.0014)	0.98(0.0015)	0.97(0.0017)	0.99(0.0015)	0.98(0.0012)	0.98(0.0012)	0.98(0.0013)	0.25(0.0254)
	SVM-SMOTE	0.97(0.0018)	0.99(0.0002)	0.98(0.0002)	0.98(0.0012)	0.99(0.0010)	0.98(0.0009)	0.98(0.0009)	0.97(0.0010)	0.25(0.017)
DT	Original	0.26(0.5799)	0.94(0.0046)	0.14(0.0295)	0.96(0.0045)	0.90(0.0061)	0.60(0.0282)	0.45(0.0135)	0.25(0.0086)	0.35(0.0583)
	SMOTE	0.94(0.0059)	0.92(0.0058)	0.92(0.0055)	0.94(0.0052)	0.93(0.0035)	0.93(0.0035)	0.93(0.0036)	0.93(0.0037)	0.65(0.0322)
	B-SMOTE1	0.93(0.0048)	0.93(0.0057)	0.93(0.0054)	0.93(0.0047)	0.93(0.0033)	0.93(0.0032)	0.93(0.0033)	0.93(0.0032)	0.64(0.0303)
	B-SMOTE2	0.92(0.0067)	0.91(0.0076)	0.91(0.0072	0.93(0.0060)	0.91(0030)	0.92(0.0028)	0.91(0.0030)	0.91(0.0031)	0.82(0.0242)
	SMOTE-NC	0.94(0.0043)	0.97(0.0045)	0.97(0.0045)	0.95(0.0038)	0.96(0.0024)	0.96(0.0023)	0.96(0.0024)	0.96(0.0025)	0.80(0.0150)
	SVM-SMOTE	0.95(0.0042)	0.94(0.0062)	0.91(0.0080)	0.97(0.0029)	0.94(0.0041)	0.94(0.0037)	0.94(0.0038)	0.93(0.0048)	0.58(0.0311)
XGBoost	Original	0.99(0.0026)	0.45(0.0122)	0.13(0.0070)	0.99(0.0007)	0.49(0.0116)	0.72(0.061)	0.66(0.0109)	0.22(0.0107)	0.99(0.0006)
	SMOTE	0.99(0.0021)	0.96(0.0043)	0.96(0043)	0.98(0.0019)	0.97(0.0021)	0.97(0.0020)	0.97(0.0020)	0.97(0.0021)	0.64(0.0352)
	B-SMOTE1	0.98(0.0026)	0.96(0.0041)	0.96(0.0039)	0.98(0.0029)	0.97(0.0021)	0.97(0.0020)	0.97(0.0021)	0.97(0.0020)	0.64(0.0362)
	B-SMOTE2	0.96(0.0033)	0.94(0.0040)	0.94(0.0042)	0.96(0.0033)	0.95(0.0022)	0.95(0.0021)	0.95(0.0022)	0.95(0.0023)	0.60(0.0314)
	SMOTE-NC	1(0)	1(0)	1(0)	1(0)	1(0)	1(0)	1(0)	1(0)	NA
	SVM-SMOTE	0.97(0.0057)	0.96(0.0042)	0.94(0.0062)	0.98(0.0038)	0.96(0.0030)	0.96(0.0029)	0.96(0.0031)	0.95(0.0038)	0.67(0.0319)

SVM Support vector machine, ANN Artificial neural network, NB Naïve bayes, RF Random forest, DT Decision tree, XGBoost extreme gradient boosting, SMOTE Synthetic minority over-sampling technique, B-SMOTE1 Borderline-SMOTE1, B-SMOTE-2 Borderline-SMOTE2, PPV Positive predictive value, NPV Negative predictive value, AUC Area under the curve

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