Deep learning fundus photo analysis screens for anemia with high accuracy.
Transforming Fundus Photography for Deep Learning-Based Anemia Screening.
Taeseen Kang, Kiyup Nam
Journal of clinical medicine · Jul 2026 · Q2 in General Medicine
Purpose
This study aimed to develop and evaluate a noninvasive anemia screening method using fundus photographs analyzed by deep learning models, by transforming circular fundus photographs into square images suitable for convolutional neural network analysis.
Methods
A total of 39,036 fundus images and clinical data collected from 2011 to 2023 were used.
n = 39,036 fundus images
Results
0.893
higher score means the eye-scan test more reliably distinguishes anemia from no anemia
n = 39,036 fundus images
More results
Among preprocessing methods, the stretching method yielded the most accurate predictions.
“
Conclusion
Deep learning analysis of fundus photographs demonstrates potential as a noninvasive screening method for anemia. This approach may be particularly beneficial for patients requiring regular hemoglobin monitoring.