©The Author(s) 2025.
World J Psychiatry. Sep 19, 2025; 15(9): 108359
Published online Sep 19, 2025. doi: 10.5498/wjp.v15.i9.108359
Published online Sep 19, 2025. doi: 10.5498/wjp.v15.i9.108359
Table 5 Test results of our proposed convolutional neural network for our collected dataset, n (%)
| Dataset | Class | Accuracy | Sensitivity | Specificity | Precision | F1-score | AUROC |
| From left to right | Healthy control | 97.49 | 96.92 | 97.84 | 96.55 | 96.74 | 97.38 |
| Schizophrenia | 97.84 | 96.92 | 98.07 | 97.95 | 97.38 | ||
| Overall | 97.38 | 97.38 | 97.31 | 97.35 | 97.38 | ||
| From top to bottom | Healthy control | 98.96 | 98.08 | 99.52 | 99.22 | 98.65 | 98.80 |
| Schizophrenia | 99.52 | 98.08 | 98.81 | 99.16 | 98.80 | ||
| Overall | 98.80 | 98.80 | 99.02 | 98.91 | 98.80 |
- Citation: Kaya MK, Arslan S, Kaya S, Tasci G, Tasci B, Ozsoy F, Dogan S, Tuncer T. Self-AttentionNeXt: Exploring schizophrenic optical coherence tomography image detection investigations. World J Psychiatry 2025; 15(9): 108359
- URL: https://www.wjgnet.com/2220-3206/full/v15/i9/108359.htm
- DOI: https://dx.doi.org/10.5498/wjp.v15.i9.108359