人工智能深度学习诊断与预测青光眼的研究进展

Research Progress of Artificial Intelligence and Deep Learning in Diagnosis and Prediction of Glaucoma

近年来,人工智能(AI)技术在青光眼的诊断和管理领域展现出显著潜力。AI能够通过深度学习算法,尤其是卷积神经网络高效分析眼底照相、光学相干断层扫描和标准视野自动检查等临床数据,从而提高青光眼及其引发的视神经损伤的检测灵敏度和特异度,提供更全面的视功能信息,有助于青光眼的早期识别和进展监测;同时,AI技术还能够预测青光眼患者的手术风险,帮助医师在术前制订干预措施。此外,应用AI技术实施的远程医疗能提高偏远地区患者的就诊便利性并降低其就医成本。

In recent years,artificial intelligence(AI)technology has shown significant potential in the diagnosis and management of glaucoma.AI can efficiently analyze various clinical data such as fundus photography,optical coherence tomography,and automatic examination of standard field of view through deep learning algorithms,especially convolutional neural networks,thereby improving the detection sensitivity and specificity of glaucoma and its associated optic nerve damage,providing more comprehensive visual function information,and helping with the early identification and progression monitoring of glaucoma.Meanwhile,AI technology can also predict the surgical risks of glaucoma patients and help the physicians develop intervention measures before surgery.In addition,remote healthcare implemented with AI technology can improve the convenience of medical treatment for patients in remote areas and reduce their medical costs.