Extracting features from normal corneas and keratoconus based on wavelet analysis

Keratoconus Diagnosis: From Fundamentals to Artificial Intelligence: A Systematic Narrative Review

“…In this review, we provide a state-of-the-art, all-encompassing assessment of the indices (combination variables in addition to the value of integrated instrument characteristics) and highlight the significant shortcomings that must be addressed before any machine learning strategy can be used more effectively in early KC detection. [17,20,[25][26][27][28][29]32,37,41,[47][48][49]56,75,86,91,95,118,119,[130][131][132][137][138][139][140][141][142][143][144][145][146][147][148][149].…”

“…Patients (p); Eyes (e); Group (g); KC group (KCG); control group (CG); Normal (Nl); Follow up (F/U); Keratoconus (KC); Clinical KC (CKC); Subclinical KC (SKC); Advanced KC (AKC); very asymmetric ectasia (VAE); Very Asymmetric Ectasia but with Normal Corneal Topography (VAE-NTG); Ocular Surface Disorders (OSD); Epithelial Basement Membrane Dystrophy (EBMD); Dry Eye Disease (DED); Keratitis Precipitate (KP), Subepithelial Opacity (SEO); Area Under the Curve (AUC); Area Under the Receiver Operator Characteristic Curve (AUROCC); Accuracy (AC); Sensitivity (Sen); Specificity (Spe); Recall (R); Purity (Pu); Belin–Ambrósio Deviation Index (BAD-D); Corneal Tomography Multivariate Index (CTMVI); Pentacam Topographical KC Classification (TKC); Tomographic–Biomechanical Parameter (TBI); Zernike Coefficients (ZC); Corneal Epithelial Thickness (ET); Deformation Amplitude (DA); Peak Distance (PD) at the Highest Concavity; Boosted Ectasia Susceptibility Tomography Index (BESTi); Multiple Logistic Regression Analysis (MLRA); Artificial intelligence (AI); Paraconsistent Feature Engineering (PFE); Support Vector Machine (SVM); Pentacam Random Forest index (PRFI); Artificial Neural Network (ANN); Flower Pollination Algorithm (FPA); Random Forest (RF); Radial Basis Function NN (RBFNN); Particle Swarm Optimization (PSO); Fractional Order PSO (FPSO); Discrete PSO (DPSO); Linear Regression (LR); Time Delay Neural Network (TDNN); Convolutional NN (CNN); Feedforward Neural Network (FNN); Multilayer Perceptron (MLP); Local Binary Pattern (LBP); Local Directional Pattern (LDP); Local Optimal Oriented Pattern (LOOP); Cat Swarm Optimization (CSO); Linear Discriminant Analysis (LDA); Principal Component Analysis (PCA); Quadratic Discriminant Analysis (QDA); Masked Face Analysis (MAFA); Anterior Segment Optical Coherence Tomography (AS-OCT); Photorefractive Keratectomy (PRK); Phototherapeutic Keratectomy (PTK); Penetrating Keratoplasty (PK); Lamellar Keratoplasty (LK); Laser-Assisted In Situ Keratomileusis (LASIK); Post-LASIK Ectasia (PLE). [ 17 , 20 , 25 , 26 , 27 , 28 , 29 , 32 , 37 , 41 , 47 , 48 , 49 , 56 , 75 , 86 , 91 , 95 , 118 , 119 , 130 , 131 , 132 , 137 , 138 , 139 ,…”

“…Moreover, a support vector machine (SVM) improved AUROC to 0.948, gaining 5.7% sensitivity, 6.9% specificity, and 10.2% accuracy using Deformation Amplitude and Peak Distance at the highest concavity when classifying normal and KC eyes [ 132 ]. ANN and the finite element method were utilized in another study to evaluate the clinical data of the Pentacam and the Corvis.…”