Blindness Detection – A Systematic Research

The proposed framework merges Generative Adversarial Networks (GANs) with Reinforcement Learning (RL) techniques to enhance blindness detection. GANs generate synthetic retinal images covering various eye diseases, enriching training data and improving generalization. RL optimizes screening strategies dynamically, adjusting decisions based on evolving patient profiles and environmental cues. Empirical evaluations on real-world datasets demonstrate superior performance over conventional methods, addressing data imbalance and fostering adaptable screening policies. This synergistic fusion offers a comprehensive, adaptable, and interpretable approach to early diagnosis and preventive care, highlighting the potential of advanced AI techniques in healthcare.