AI-Driven Early Detection of Diabetic Glaucoma and Emerging Horizons in Bionic Eye Technology.

Q4 Medicine
Gaurav Tiwari, Ankita Wal, Raghuraj Singh Suryavanshi, Rishi Shukla, Muzammil Khan, Brijesh Kumar Chaurasia
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Abstract

Background: Diabetic glaucoma is a serious eye disorder that can lead to permanent vision loss and is increasingly seen in individuals with long-term diabetes. With its rising global incidence, there is a critical need for early and reliable methods of detection to prevent severe complications.

Objective: This study highlights the growing role of artificial intelligence (AI), especially deep learning technologies, in identifying diabetic glaucoma at an early stage. It also reviews progress in bionic eye technologies designed to help restore vision in affected individuals.

Methods: Relevant scientific literature was reviewed by searching databases including PubMed, Taylor francis, ScienceDirect, MDPI, and Bentham. Articles published up to 2025 were considered, focusing on terms such as "diabetic glaucoma,""retinal imaging,""deep learning,""AI in eye care,""bionic eye,"and "neuroprosthetics."Studies were selected based on their relevance to diagnostic innovations and vision-restoration technologies.

Results: Recent developments in AI have enabled more accurate interpretation of retinal images, such as those from fundus cameras and optical coherence tomography (OCT), aiding in early detection of structural changes linked to glaucoma. At the same time, bionic eye systems-based on neuroprosthetic implants-are showing promise in partially restoring vision in cases of severe visual impairment.

Conclusion: Combining AI-powered diagnostics with emerging bionic eye technologies represents a major shift in managing diabetic glaucoma. These innovations have the potential to improve early detection and offer new options for visual rehabilitation, paving the way for more effective patient care in ophthalmology.

人工智能驱动的糖尿病性青光眼早期检测及仿生眼技术的新兴领域。
背景:糖尿病性青光眼是一种严重的眼部疾病,可导致永久性视力丧失,在长期糖尿病患者中越来越常见。随着其全球发病率的上升,迫切需要早期和可靠的检测方法,以预防严重并发症。目的:本研究强调人工智能(AI),特别是深度学习技术在早期识别糖尿病青光眼方面的作用越来越大。它还回顾了仿生眼技术的进展,这些技术旨在帮助受影响的人恢复视力。方法:检索PubMed、Taylor francis、ScienceDirect、MDPI、Bentham等数据库,回顾相关科学文献。在2025年之前发表的文章被纳入考虑范围,重点关注“糖尿病性青光眼”、“视网膜成像”、“深度学习”、“人工智能眼科护理”、“仿生眼”和“神经假肢”等术语。“研究的选择是基于它们与诊断创新和视力恢复技术的相关性。结果:人工智能的最新发展使视网膜图像能够更准确地解释,例如眼底相机和光学相干断层扫描(OCT),有助于早期发现与青光眼相关的结构变化。与此同时,基于神经假体植入的仿生眼系统在部分恢复严重视力障碍患者的视力方面显示出了希望。结论:将人工智能诊断与新兴的仿生眼技术相结合,代表了糖尿病性青光眼治疗的重大转变。这些创新有可能改善早期发现,并为视力康复提供新的选择,为眼科更有效的患者护理铺平道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
0.70
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