Table 1.

Summary of the 26 published studies that included the use of machine learning for the detection of subclinical keratoconus.

Study	System	Number of eyes		Fellow eyea	Input types	Method	Results (%)
		Normal	Subclinical keratoconus				Sensitivity	Specificity
Arbelaez et al [47]	Sirius	1259	426	No	Elevation, keratometry, pachymetry, and aberrometry	SVMb	92	97.7
Saad et al [48]	Orbscan	69	34	No	Pachymetry, keratometry, elevation, and Displacement	DAc	92	96
Smadja et al [49]	GALILEI	177	47	Yes	Keratometry, pachymetry, elevation, aberrometry, demographic, and indices	DTd	93.6	97.2
Ramos-Lopez et al [50]	CSO topography system	50	24	No	Elevation and displacement	Linear regression	33	78
Cao et al [14]	Pentacam	39	49	No	Keratometry, pachymetry, and demographic	RFe, SVM, K-nearest neighbors, LoRf, DA, Lasso regression, DT, and NNg	94	90
Buhren et al [51]	Orbscan IIz	245	32	No	Keratometry, pachymetry, aberrometry, and elevation	DA	78.1	83.3
Chan et al [52]	Orbscan IIz	104	24	Yes	Pachymetry, keratometry, elevation, and displacement	DA	70.8	98.1
Kovacs et al [53]	Pentacam	60	15	Yes	Keratometry, pachymetry, elevation, indices, and displacement	NN	90	90
Saad et al [54]	OPD-scan	114	62	Yes	Keratometry, aberrometry, and indices	DA	63	82
Ruiz Hidalgo et al [55]	Pentacam HR	194	67	No	Keratometry, pachymetry, and aberrometry	SVM	79.1	97.9
Ruiz Hidalgo et al [56]	Pentacam HR	44	23	No	Keratometry, pachymetry, and indices	SVM	61	75
Xu et al [57]	Pentacam HR	147	77	Yes	Pachymetry, elevation, and keratometry	DA	83.7	84.5
Ambrosio et al [58]	Pentacam+Corvis ST	480	94	Yes	Pachymetry, elevation, keratometry, and Biomechanical	RF, SVM, and LoR	90.4	96
Sideroudi et al [59]	Pentacam	50	55	No	Keratometry	LoR	91.7	100
Francis et al [60]	Corvis ST	253	62	Yes	Biomechanical	LoR	90	91
Yousefi et al [61]	SS-1000 CASIA	1970	796	No	Elevation, pachymetry, and aberrometry	Unsupervised	88	14
Lopes et al [62]	Pentacam HR	2980	188	Yes	Pachymetry, elevation, indices, and displacement	DA, SVM, naive Bayes, NN, and RF	85.2	96.6
Steinberg et al [63]	Pentacam+Corvis ST	105	50	Yes	Pachymetry, elevation, keratometry, and biomechanical	RF	63	83
Issarti et al [64]	Pentacam	312	90	Yes	Elevation and pachymetry	NN	97.8	95.6
Chandapura et al [65]	RCTVue+Pentacam	221	72	Yes	Keratometry, elevation, pachymetry, aberrometry, and indices	RF	77.2	95.6
Xie at al [66]	Pentacam HR	1368	202	No	Heat maps	CNNh	76.5	98.2
Kuo et al [67]	TMS-4+Pentacam+Corvis ST	170	28	No	Heat maps	CNN	28.5	97.2
Shi et al [68]	Pentacam+ultrahigh resolution optical coherence tomography	55	33	Yes	Keratometry, elevation, pachymetry, indices, and demographic	NN	98.5	94.7
Toprak et al [69]	MS-39	66	50	Yes	Keratometry, pachymetry, and displacement	LoR	94	98.5
Issarti et al [70]	Pentacam HR	304	117	Yes	Elevation and Pachymetry	NN	85.2	70
Lavric et al [71]	SS-1000 CASIA	1970	791	No	Keratometry, pachymetry, and aberrometry	25 machine learning methods compares	89.5	96

^aFellow eye indicates whether the study defined subclinical keratoconus as the fellow eye of an individual with apparently unilateral keratoconus, with no clinical or topographical features of keratoconus.

^bSVM: support vector machine.

^cDA: discriminant analysis.

^dDT: decision tree.

^eRF: random forest.

^fLoR: logistic regression.

^gNN: neural network.

^hCNN: convolutional neural network.