Authors | Year | Instruments | ML classifier | Subjects | Results |
---|---|---|---|---|---|
Current Study | 2019 | UHR-OCT, Scheimpflug camera | Neural network | 38 eyes with KC, 33 eyes with subclinical KC, 50 normal eyes | 93% precision for subclinical KC eyes, 99% precision for KC eyes |
Smolek et al. [9] | 1997 | Corneal topography | Neural network | 6 KC suspect eyes, 33 eyes with KC | 100% accuracy, sensitivity and specificity for all KC suspect and KC eyes |
Accardo et al. [24] | 2002 | Corneal topography | Neural network | 120 eyes with early KC eyes, 120 normal eyes | 94.1% sensitivity, 97.6% specificity for early KC eyes |
Arbelaez et al. [11] | 2012 | Scheimpflug camera and Placido corneal topography | SVM | 877 eyes with KC, 426 eyes with subclinical KC, 1259 healthy control eyes | 98.2% accuracy (95.0% sensitivity and 99.3% specificity) for KC eyes and 97.3% accuracy (92.0% sensitivity and 97.7% specificity) for subclinical KC eyes |
Smadja et al. [10] | 2013 | Scheimpflug camera | Decision tree | 148 eyes with KC, 177 eyes with forme fruste KC, 372 healthy control eyes | 100% sensitivity and 99.5% specificity for KC eyes, 93.6% sensitivity and 97.2% specificity for forme fruste KC eyes |
Kovacs et al. [25] | 2016 | Scheimpflug camera | Neural network | 60 eyes with KC, 15 eyes with preclinical KC, 60 healthy control eyes | 0.99 AUC, 100% sensitivity and 98% specificity for KC eyes, 0.96 AUC, 92% sensitivity and 85% specificity for preclinical KC eyes |
Saad et al. [26] | 2016 | Placido based corneal topography and corneal wavefront measurements | Neural network | 62 eyes with forme fruste KC, 114 normal eyes | 0.97 AUC, 63% sensitivity and 82% for forme fruste KC, 100% sensitivity and 82% specificity for KC eyes |
Hidalgo et al. [27] | 2016 | Scheimpflug camera | SVM | 454 eyes with KC, 67 eyes with forme fruste KC, 194 normal eyes | 98.9% accuracy, 99.1% sensitivity and 98.5% specificity for KC eyes, 93.1% accuracy, 79.1% sensitivity and 97.7% specificity for forme fruste KC eyes |
Ambrosio et al. [21] | 2017 | Scheimpflug camera and biomechanical camera | SVM, random forest | 111 eyes with KC, 227 normal eyes | 1.0 AUC for KC eyes |
Lopes et al. [12] | 2018 | Scheimpflug camera | Random forest | 71 eyes with ectasia susceptibility, 182 eyes with KC, 2980 normal eyes | 85.2% sensitivity and 0.966 specificity, 0.968 AUC for suspected KC eyes. |
Issarti et al. [28] | 2019 | Scheimpflug camera | Neural network | 77 eyes with suspect KC, 312 normal eyes | 96.56% accuracy, 97.78% sensitivity and 95.56% specificity for suspect KC eyes |