Table 6.

The complete table about nodular signs, data analysis methods, prediction models, system evaluation and other information

Section in this paper	Nodular signs	Data analysis methods	Prediction models	System evaluation	Data sets	Nodule style	Literature
Nodular signs	Nodule size	Student’s t test, Chi square test or Fisher’s exact test		Univariate and multivariate analyses	Private	GGNs	[6]
	Nodule size, smoking history	Student’s t test, Chi square test		Simple linear regression analysis	Private	GGNs	[7]
	Nodule size	Chi square test		Logistic regression method	Private	Solid nodules, mGGO, pGGO	[8]
	Nodule size, smoking history, lung cancer history				Private	Solid nodules, mGGO, pGGO	[12]
	Nodule size, lobulation and spiculation, vascular convergence sign, lung cancer history, smoking history				Private	mGGO, pGGO	[14]
	Nodule size, lobulation and spiculation, solid components proportion, smoking history, lung cancer history	Student’s t test, Chi square test			Private	pGGO	[15]
	Nodule size, lung cancer history, smoking history, lobulation and spiculation, pleural indentation	Student’s t test, Fisher’s exact test, Chi squared test		Logistic regression models	Private	Solid nodules, mGGO, pGGO	[17]
	Nodule size, solid components proportion, lobulation and spiculation, air bronchogram	Chi square test, Fisher’s exact test		Linear regression model	Private	GGNs	[18]
	Lobulation and spiculation, vascular convergence sign, solid components proportion, pleural indentation	Student’s t test, Chi square test			Private	mGGO, pGGO	[19]
	Pleural indentation	Chi square test			Private	mGGO, pGGO	[20]
	Nodule size, lobulation and spiculation, air bronchogram, smoking history	Chi square test or Fisher’s exact test, Student’s t test		Multivariate analysis, ROC	Private	pGGO	[21]
Data analysis methods	Nodule size	Volume doubling time, mass doubling time		Linear regression analysis	Private	GGNs	[27]
	Nodule size	Mass doubling time, Student’s t test			Public: NELSON	GGNs	[28]
	Nodule size	Diffusion kurtosis imaging		AUC, ROC	Private	Solid nodules, GGNs	[29]
	Lobulation and spiculation	Differential geometry-based		Percent change and proportional change	Public: LIDC-IDRI	Pulmonary nodules	[30]
	Nodule size, lobulation and spiculation	Support vector machine			Public: LIDC-IDRI	Pulmonary nodules	[31]
	Lobulation and spiculation	Weighted rule based		Leave-one-out procedure	Public: LIDC-IDRI	Pulmonary nodules	[32]
Prediction models	Nodule size, smoking history, lobulation and spiculation	Student’s t test	Mayo clinic model	AUC, ROC	Private	Pulmonary nodules	[33]
	Nodule sizer, lobulation and spiculation, solid components proportion, smoking history		Modified model	ROC, univariate analysis, multivariate analysis, stepwise logistic regression, multivariable logistic regression	Private	Solid nodules, GGNs	[35]
	Nodule size, lobulation and spiculation, lung cancer history	Student’s t test, Chi square test	PanCan model, Lung-RADS, NCCN guidelines	AUC, ROC	Public: DLCST	Solid nodules, mGGO, pGGO	[37]
	Nodule size, lobulation and spiculation	Machine learning	MC-CNN	AUC	Public: LIDC-IDRI	Pulmonary nodules	[41]
		Deep learning, machine learning	MTANNs, CNNs	AUC, FROC, ROC	Public	Pulmonary nodules	[42]
System evaluation	Nodule size, lobulation and spiculation, air bronchogram, pleural indentation, vascular convergence sign			Binary logistic regression analysis, ROC	Private	pGGO	[43]
	Nodule size, solid components proportion, lobulation and spiculation, air bronchogram	Nodule growth rate or volume-doubling time		Volumetry	Public: LIDC-IDRI	Solid nodules, GGNs	[44]
	Nodule size, lobulation and spiculation, smoking history	Student’s t test, Chi square test		Volumetry	Private	Solid nodules, GGNs	[45]
	Nodule size, solid components proportion, smoking history, lung cancer history	Chi square test or Fisher’s exact test		Cox proportional hazards and logistic regression models, univariate and multivariate analyses	Private	GGNs	[46]
	Nodule size, solid components proportion			Volumetric automated computer-assisted analytic program, Cox proportional hazards and logistic regression models, multiple logistic regression analysis, univariate analysis, multiple analyses, ROC	Private	Solid nodules, mGGO, pGGO	[47]
	Nodule size, lobulation and spiculation, smoking history			Poisson regression, descriptive analysis, multivariable logistic regression models, multivariate analysis	Private	Solid nodules, mGGO, pGGO	[48]
	Lobulation and spiculation	Support vector machine, hypothesis t test		Quantitative comparison measures, AUC, ROC	Public: LIDC-IDRI	Pulmonary nodules	[49]
Nodular signs, data analysis methods	Nodule size, lobulation and spiculation, pleural indentation, smoking history	Nomogram		Univariate analysis, multivariate analysis	Private	pGGO	[13]
Nodular signs, Prediction models	Nodule size, lung cancer history, lobulation and spiculation	Student’s t test, Fisher’s exact test	PanCan model	ROC, AUC, multivariable logistic regression analyses	Public: DLCST	Solid nodules, mGGO, pGGO	[16]
Nodular signs, system evaluation	Nodule size, solid components proportion, vascular convergence sign, lobulation and spiculation	Student’s t test, Chi square test		Binary logistic regression analysis	Private	GGNs	[9]
	Nodule size, lobulation and spiculation	Liner classifier		AUC, ROC	Private	Pulmonary nodules	[10]
	Lobulation and spiculation	Chi square test		Generalized estimating equation analyses, multivariate analysis	Private	Pulmonary nodules	[11]
	Nodule size, lobulation and spiculation, air bronchogram	Chi square test, Fisher exact test		One-way analysis of variance, ROC, correlation analysis	Private	pGGO	[22]
Data analysis methods, system evaluation	Nodule size, lobulation and spiculation	Kurtosis and skewness of density histogram		ROC, Bland–Altman analysis	Private	Solid nodules, mGGO	[26]

Italics text means main emphasis of the corresponding literature