Table 4.

Model performance comparison between the ophthalmologists.

Accuracy	A	A + B	A + B + C
Ophthalmology residents
1	0.4897	0.5714	0.6530
2	0.6734	0.7346	0.6938
3	0.5306	0.5714	0.7142
Intergrader Agreement (Kappa)	0.0383	0.1868	0.4086
Retina specialists
1	0.6326	0.8163	0.8163
2	0.7142	0.6938	0.8136
3	0.7142	0.7551	0.8775
Intergrader Agreement (Kappa)	0.3562	0.4302	0.6649
Ophthalmologists average	0.6257	0.6904	0.7614
Our proposed model	0.6939	0.7142	0.8163

The patients’ spectral-domain optical coherence tomography images captured before injection, after the first injection, and after the second injection are denoted as A, B, and C, respectively. Both ophthalmologists and our proposed model used these images as inputs to predict the results. Fleiss’ kappa scores were used to calculate intergrader agreement, revealing that agreement improved as more OCT images were provided. The AI model consistently demonstrated higher predictive accuracy compared to both resident and specialist groups across all conditions. Additionally, the p-value confirmed that the observed improvements in agreement were statistically significant, with a p-value of 0.05 or lower for intergrader agreements exceeding 0.1.

Significant values are in [bold].