Table 3.
Summary of data description, main methods, applications, and evaluation in relevant dry eye studies
| Study | Data description | Main methods | Applications | Evaluation |
|---|---|---|---|---|
| Grus and Augustin22 | Numerical data: Tear protein | ANN | AE; diagnosis | ACC: 89% |
| Grus et al.23 | Numerical data: Tear proteins | ANN | AE; diagnosis | AUC: 93% |
| Yedidya et al.24 | Images and videos: Tear film | IPT | AE; diagnosis | ACC: 91% |
| Koh et al.25 | Images: Meibomian gland imaging images | SVM | AE; diagnosis | SPE: 96%, SEN: 98% |
| Rodriguez et al.26 | Images: Conjunctiva | IPT | AE; diagnosis | ACC >64% |
| Ramos et al.27 | Images and videos: Tear film videos | IPT | AE; diagnosis | SPE: 80%, SEN: 82% |
| Rodriguez et al.28 | Images: Fluorescently stained corneal images | IPT | AE; diagnosis | CCC: 93% |
| Remeseiro et al.29 | Images: Tear film interferometry images | IPT | AE; diagnosis | ACC: 96% |
| Remeseiro et al.30 | Images: Tear film map | SVM | AE; diagnosis | ACC: 91% |
| Peteiro-Barral et al.31 | Images: Tear film lipid layer images | Multiple criteria decision-making | Diagnosis | NR |
| Hwang et al.32 | Images: Tear film lipid layer | IPT | Diagnosis | NR |
| Baǧbaba et al.33 | Images: Fluorescein-stained cornea images | IPT | Diagnosis | CCC: 98% |
| Fernández et al.34 | Numerical and categorical data: Tear sample | LR | IRF | AUC: 74% |
| Cartes et al.35 | Numerical data: Tear film osmolarity | Logistic classifier | AE | ACC: 85% |
| Yang et al.36 | Numerical and categorical data: Questionnaire | ANN | IRF | AUC: 79% |
| Nam et al.37 | Numerical and categorical data | Decision trees | IRF | AUC: 70% |
| da Cruz et al.38 | Images: Tear film lipid layer | RF | Diagnosis | ACC: 97% |
| da Cruz et al.39 | Images: Tear film | RF | AE | ACC: 99% |
| Ćirković40 | Numerical and categorical data: Virtual patient | NR | Diagnosis; treatment | NR |
| Zhou et al.41 | Images: Meibomian gland images | CNN | AE; diagnosis | ACC: 92% |
| Stegmann et al.42 | Images: Tear meniscus | CNN | AE | SPE: 98% SEN: 96% |
| Wang et al.43 | Images: OCT images | CNN | AE | DSC: 97% |
| Setu et al.44 | Images: Meibography images | CNN | AE | AUC: 96% |
| Elsawy et al.45 | Images: OCT images | CNN | Diagnosis | AUC: 99% |
| Chase et al.46 | Images: OCT images | CNN | Diagnosis | ACC: 85% |
| Xu et al.47 | Images: IVCM images | CNN | AE | AUC: 96% |
| Wang et al.48 | Images: Anterior segment images | CNN | AE | AUC >90% |
| Zheng et al.49 | Images: Blink videos | CNN | AE; diagnosis | DSC >90% |
| Yu et al.50 | Images: Meibography images | CNN | AE; diagnosis | ACC: 92% |
| Saha et al.51 | Images: Meibography images | GAN | AE; diagnosis | ACC: 73% |
| Fineide et al.52 | Numerical and categorical data: DE patients | RF, multilayer perceptron | AE; IRF | ACC >97% |
| Deng et al.53 | Images: Meibography images | CNN | AE; diagnosis | DSC >69% |
| Jing et al.54 | Images: IVCM images | CNN | AE | NR |
| Zhang et al.55 | Images: Meibography images | CNN | AE; diagnosis | DSC: 93% |
| Jing et al.56 | Images, numerical and categorical data: IVCM images | CNN | AE | NR |
| Zhang et al.57 | Images and numerical data: Blink videos | CNN | AE; diagnosis | ACC >96% |
| Jing et al.58 | Images and numerical data: Questionnaire, IVCM images | CNN | AE | NR |
| Edorh et al.59 | Numerical and categorical data: Corneal epithelial thickness | RF; LR | AE | NR |
| Shimizu et al.60 | Images and videos: DE videos | CNN | AE; diagnosis | AUC: 88% |
| Levine et al.61 | Images: IVCM images of the cornea | CNN | AE | NR |
| Kikukawa et al.62 | Images: Tear film | CNN | AE; diagnosis | AUC: 90% |
| Abdelmotaal et al.63 | Images: Ocular surface videos | CNN | AE; diagnosis | AUC: 98% |
| Yokoi et al.64 | Videos: Keratography data | CNN | AE; diagnosis | ACC >72% |
| Storås et al.65 | Numerical and categorical data: Tear proteins | LGBM classifier | AE; diagnosis | ACC >72% |
| Li et al.66 | Images, numerical and categorical data: Meibography images | CNN | AE; diagnosis | NR |
| Wang et al.67 | Images: Tear meniscus height | CNN | AE; diagnosis | DSC: 99% |
| Wan et al.68 | Images: Ocular surface images | CNN | AE; diagnosis | DSC: 88% |
| Wang et al.69 | Images: Meibography images | CNN | Diagnosis | AUC >93% |
DE: Dry eye, NR: Not reported, AE: Ancillary examination, IRF: Identification of risk factors, ANN: Artificial neural network, SVM: Support vector machines, IPT: Image processing technique, LR: Logistic regression, RF: Random forest, CNN: Convolutional neural networks, GAN: Generative adversarial network, ACC: Accuracy, AUC: Area under curve, SPE: Specificity, SEN: Sensitivity, CCC: Concordance correlation coefficient, DSC: Dice similarity coefficient, OCT: Optical coherence tomography, IVCM: In vivo confocal microscop