无需重训练的AI眼科影像平台，跨机构诊断准确率超90%
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers
- 采用无训练局部特征增强技术，自动适应不同设备与人群数据
- 在5个中国中心、越南、新加坡和英国测试中，疾病识别准确率达86%以上
- 界面友好且可量化诊断置信度，适合临床医生直接使用
人工智能在医学影像诊断中展现巨大潜力，但现有模型在不同临床场景下需重新训练，限制了推广。我们提出GlobeReady平台，实现无需重训练、微调或技术专长即可进行眼底疾病诊断。该平台在11种眼底病上使用彩色眼底照片（CPFs）的准确率为93.9-98.5%，在15种眼底病上使用光学相干断层扫描（OCT）的准确率为87.2-92.7%。通过训练-free本地特征增强，有效缓解中心间和人群间的域偏移，在中国5个中心平均准确率88.9-97.4%，越南86.3-96.9%，新加坡73.4-91.0%，英国90.2-98.9%。内置置信度量化机制进一步提升准确率至94.9-99.4%（CPFs）和88.2-96.2%（OCT），并能以86.3%准确率识别49种常见与罕见眼底病的分布外样本（CPFs），OCT对13种疾病的识别准确率达90.6%。多国临床医生评分高达4.6/5，认为其易用性和临床相关性强。
原文摘要 · Abstract (English)
Artificial intelligence (AI) shows remarkable potential in medical imaging diagnostics, yet most current models require retraining when applied across different clinical settings, limiting their scalability. We introduce GlobeReady, a clinician-friendly AI platform that enables fundus disease diagnosis that operates without retraining, fine-tuning, or the needs for technical expertise. GlobeReady demonstrates high accuracy across imaging modalities: 93.9-98.5% for 11 fundus diseases using color fundus photographs (CPFs) and 87.2-92.7% for 15 fundus diseases using optic coherence tomography (OCT) scans. By leveraging training-free local feature augmentation, GlobeReady platform effectively mitigates domain shifts across centers and populations, achieving accuracies of 88.9-97.4% across five centers on average in China, 86.3-96.9% in Vietnam, and 73.4-91.0% in Singapore, and 90.2-98.9% in the UK. Incorporating a bulit-in confidence-quantifiable diagnostic mechanism further enhances the platform's accuracy to 94.9-99.4% with CFPs and 88.2-96.2% with OCT, while enabling identification of out-of-distribution cases with 86.3% accuracy across 49 common and rare fundus diseases using CFPs, and 90.6% accuracy across 13 diseases using OCT. Clinicians from countries rated GlobeReady highly for usability and clinical relevance (average score 4.6/5). These findings demonstrate GlobeReady's robustness, generalizability and potential to support global ophthalmic care without technical barriers.
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