AI-Driven Myopia Prevention 3.0: Risk Stratification and Personalized Intervention
A new arXiv paper (2607.24187) proposes Myopia Prevention and Control 3.0, an AI-driven framework to address the projected myopia epidemic affecting half the world's population by 2050. The model integrates three domains: AI-driven risk stratification using machine learning on multimodal data, AI-enabled proactive monitoring via wearables and smartphones, and AI-powered personalized intervention with closed-loop feedback. This moves beyond conventional school-based screening (Phase 1.0) and risk factor management (Phase 2.0). The paper critically evaluates evidence across each stage, aiming to transform myopia prevention from reactive to proactive precision medicine.
Key facts
- Half the world's population will be myopic by 2050.
- Conventional approaches: school-based vision screening (Phase 1.0) and evidence-based risk factor management (Phase 2.0).
- Myopia Prevention and Control 3.0 is defined by AI integration across three domains.
- Domain 1: AI-driven risk stratification predicting individual-level risk via machine learning on multimodal data.
- Domain 2: AI-enabled proactive monitoring via wearables, smartphones, and school screening networks.
- Domain 3: AI-powered personalized intervention with closed-loop feedback.
- The paper is from arXiv with ID 2607.24187.
- The framework forms a closed-loop pipeline.
Entities
Institutions
- arXiv