FRIDAY, July 18, 2025 -- An artificial intelligence (AI) model integrated into a retina tracker for diabetic retinopathy can achieve high accuracy while being resource-efficient, according to a study presented at ENDO 2025, the annual meeting of the Endocrine Society, held from July 12 to 15 in San Francisco..

2025年7月18日，星期五——一项在2025年内分泌学会年会（ENDO 2025）上发表的研究表明，将人工智能（AI）模型集成到用于糖尿病视网膜病变的视网膜追踪器中，可以在保持高准确性的同时实现资源高效。该会议于7月12日至15日在旧金山举行。

Jansi Rani Sethuraj, R.N., from the University of Texas Health Science Center at Houston, and colleagues developed an AI-powered model integrated into the Simple Mobile AI Retina Tracker (SMART), a universally accessible application for detection, staging, and monitoring of diabetic retinopathy progression.

来自德克萨斯大学休斯顿健康科学中心的Jansi Rani Sethuraj注册护士及其同事开发了一种集成到简易移动人工智能视网膜追踪器（SMART）中的人工智能模型，这是一款用于检测、分期和监测糖尿病视网膜病变进展的普遍可访问的应用程序。

Pretrained models from deep learning architectures were trained on anonymized fundoscopic images from diverse populations with diabetes. The trained models then underwent rigorous internal validation and external validation in multiple datasets. The ability of models to differentiate diabetic retinopathy from 39 ocular conditions was examined..

深度学习架构的预训练模型使用来自不同糖尿病人群的匿名眼底图像进行训练。训练后的模型随后在多个数据集中进行了严格的内部验证和外部验证。研究还检验了这些模型区分糖尿病视网膜病变与39种眼部疾病的能力。

The researchers found that across diverse datasets, the EfficientNetB0 achieved more than 99 percent accuracy, with an image processing speed <1 second per image. The model demonstrated superior computational efficiency, with one-third runtime compared with ResNet18; across tested datasets, it maintained robust generalization (area under the receiver operating characteristic curve, >0.99).

研究人员发现，在不同的数据集上，EfficientNetB0 的准确率超过 99%，图像处理速度小于每张 1 秒。该模型展示了卓越的计算效率，运行时间仅为 ResNet18 的三分之一；在所有测试数据集中，它保持了强大的泛化能力（接收者操作特征曲线下的面积 >0.99）。

Real-world feasibility was confirmed in external evaluations..

现实世界的可行性在外部评估中得到了确认。

'The SMART AI application enables ophthalmologists to streamline patient screening, empowers primary care providers to incorporate eye exams into routine visits, and expands access to high-quality retinal assessments in regions lacking specialized ophthalmic care,' Sethuraj said in a statement.

“SMART AI应用程序使眼科医生能够简化患者筛查，使初级保健提供者能够将眼科检查纳入常规检查，并在缺乏专业眼科护理的地区扩大获得高质量视网膜评估的机会，”塞图拉吉在一份声明中表示。

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