Frontiers in Cell and Developmental Biology, Journal Year: 2025, Volume and Issue: 13
Published: April 17, 2025
Global eye health has become a critical public challenge, with the prevalence of blindness and visual impairment expected to rise significantly in coming decades. Traditional ophthalmic systems face numerous obstacles, including uneven distribution medical resources, insufficient training for primary healthcare workers, limited awareness health. Addressing these challenges requires urgent, innovative solutions. Artificial intelligence (AI) demonstrated substantial potential enhancing across various domains. AI offers significant improvements data management, disease screening monitoring, risk prediction early warning systems, resource allocation, education patient management. These advancements substantially improve quality efficiency healthcare, particularly preventing treating prevalent conditions such as cataracts, diabetic retinopathy, glaucoma, myopia. Additionally, telemedicine mobile applications have expanded access services enhanced capabilities providers. However, there are integrating into Key issues include interoperability electronic records (EHR), security privacy, bias, algorithm transparency, ethical regulatory frameworks. Heterogeneous formats lack standardized metadata hinder seamless integration, while privacy risks necessitate advanced techniques anonymization. Data biases, stemming from racial or geographic disparities, “black box” nature models, limit reliability clinical trust. Ethical issues, ensuring accountability AI-driven decisions balancing innovation safety, further complicate implementation. The future lies overcoming barriers fully harness AI, that technology translate tangible benefits patients worldwide.
Language: Английский