Table 9.

Item response theory–based electronic intensive care unit mortality prediction accuracy stratified by classification difficulty index.

Number of cases		CDIa		LRb (%)		LDAc (%)		KNNd (%)		DTe (%)		NBf (%)		NNg (%)
Balanced
	2		3.0		100.0		100.0		100.0		50.0		100.0		100.0
	61		2.5		82.0		82.0		75.4		78.7		86.9		85.2
	160		2.0		81.3		82.5		75.0		76.3		81.9		83.4
	621		1.5		86.2		86.8		74.5		79.2		83.7		87.9
	3167		1.0		83.7		82.9		72.1		78.3		66.3		85.4
	4998		0.5		74.0		72.7		64.7		73.1		55.2		80.9
	4776		0.0		70.9		70.1		58.5		71.5		57.3		80.0
	3864		−0.5		73.8		74.5		63.3		74.4		67.4		84.3
	2858		−1.0		85.4		85.5		74.4		84.8		83.1		91.8
	1183		−1.5		92.5		92.6		84.3		91.7		91.9		96.4
	240		−2.0		97.1		97.1		91.7		95.8		96.3		97.9
	10		−2.5		100.0		100.0		100.0		100.0		100.0		100.0
Imbalanced
	6		3.0		66.7		83.3		83.3		66.6		66.6		83.3
	58		2.5		82.8		81.0		69.0		75.9		87.9		84.5
	215		2.0		79.1		78.6		67.0		72.6		76.3		82.3
	1369		1.5		79.8		79.0		65.4		75.2		72.8		85.7
	4776		1.0		72.2		72.4		61.6		74.8		58.4		83.9
	6657		0.5		67.3		67.0		72.1		57.3		57.3		83.1
	7068		0.0		76.4		76.9		70.0		78.8		70.3		88.5
	6396		−0.5		87.1		87.3		83.2		87.3		83.4		93.7
	4265		−1.0		94.8		95.0		92.0		94.3		92.7		97.7
	1763		-1.5		98.0		98.0		97.1		97.9		97.3		99.4
	317		-2.0		99.1		99.1		98.4		98.4		98.4		99.1
	20		-2.5		100.0		100.0		100.0		100.0		100.0		100.0

^aCDI: classification difficulty index.

^bLR: logistic regression.

^cLDA: linear discriminant analysis.

^dKNN: K-nearest neighbor.

^eDT: decision tree.

^fNB: naive Bayes.

^gNN: neural network.