Nadarajasundaram Aaruran, Harrow Simeon
Emergency Department, St Thomas' Hospital, London, GBR.
Emergency Medicine Department, Maidstone and Tunbridge Wells NHS Trust, Maidstone, GBR.
Cureus. 2025 Jan 28;17(1):e78144. doi: 10.7759/cureus.78144. eCollection 2025 Jan.
Visual impairment and eye disease remain a significant burden, highlighting the need for further support regarding eye care services. Artificial intelligence (AI) and its rapid advancements are providing an avenue for transforming healthcare. As a result, this provides a potential avenue to address the growing challenges with eye health and could assist in settings such as eye casualty departments. This review aims to evaluate current studies on AI implementation in eye casualty triage to understand the potential application for the future. A systematic review was conducted across a range of sources and databases producing 77 records initially identified, with four studies included in the final analysis. The findings demonstrated that AI tools are able to produce consistent and accurate triaging of patients and provide improvement in work efficiency without compromising safety. However, we note limitations of the studies including limited external validations of results and general applicability at present. Additionally, all the studies highlight the need for further studies and testing to allow for better understanding and validation of AI tools in eye casualty triaging.
视力障碍和眼部疾病仍然是一个重大负担,凸显了在眼科护理服务方面提供进一步支持的必要性。人工智能(AI)及其快速发展为变革医疗保健提供了一条途径。因此,这为应对日益严峻的眼部健康挑战提供了一条潜在途径,并可能在眼科急诊部门等场所提供帮助。本综述旨在评估当前关于AI在眼科急诊分诊中应用的研究,以了解其未来的潜在应用。我们在一系列来源和数据库中进行了系统综述,最初识别出77条记录,最终分析纳入了4项研究。研究结果表明,AI工具能够对患者进行一致且准确的分诊,并在不影响安全性的情况下提高工作效率。然而,我们注意到这些研究存在局限性,包括结果的外部验证有限以及目前的普遍适用性。此外,所有研究都强调需要进一步的研究和测试,以便更好地理解和验证AI工具在眼科急诊分诊中的作用。