L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction

Zeghlache, R., Conze, P., Daho, M., Li, Y., Rezaei, A., Le Boité, H., Tadayoni, R., Massin, P., Cochener, B., Brahim, I., & others

Computers in Biology and Medicine, 2025 , 185 : 109508

Abstract

Introduction

Methods

Results

Discussion

Conclusions

Acknowledgments

Citation

Zeghlache, R., Conze, P., Daho, M., Li, Y., Rezaei, A., Le Boité, H., Tadayoni, R., Massin, P., Cochener, B., Brahim, I., and others (2025). L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction. Computers in Biology and Medicine, 185, 109508.

@article{zeghlache2025mae,
  title={L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction},
  author={Zeghlache, Rachid and Conze, Pierre-Henri and Daho, Mostafa El Habib and Li, Yihao and Rezaei, Alireza and Le Boité, Hugo and Tadayoni, Ramin and Massin, Pascal and Cochener, Béatrice and Brahim, Ikram and others},
  journal={Computers in Biology and Medicine},
  volume={185},
  pages={109508},
  year={2025},
  publisher={Pergamon},
}