基于标签的跨模态融合用于成人到儿童ECG转移 via 课程门控对比对齐
Label-Conditioned Cross-Modal Fusion for Adult-to-Pediatric ECG Transfer via Curriculum-Gated Contrastive Alignment
AI总结：
本文提出PEACE框架，通过预训练和适应性融合提升儿童ECG诊断，采用对比学习和课程适应策略，在有限标注下实现高准确率。
摘要：
自动化的儿童心电图（ECG）解释仍具挑战性，因为心率、间隔和波形的发育差异限制了主要在成人数据上训练的模型的可转移性，同时专家标注的儿童ECG数据集稀缺。我们提出PEACE（通过跨模态增强的儿童-成人ECG对齐），一个在MIMIC-IV ECG上预训练并适应于儿童目标的成人到儿童ECG转移框架。PEACE整合标签特定的双向对比学习（LSBC）以对齐ECG表示与诊断语义，并采用课程适应融合（CAF）以在有限的儿童监督下稳定优化。标签条件的短文本描述在训练期间提供辅助语义监督，而推理仅需ECG信号。在ZZU-pECG上，PEACE在零样本、50样本和全微调设置下分别达到宏平均AUCs为59.39%、81.74%和91.56%，优于ECG-only、多模态和通用领域适应基线，包括DANN和MMD。在PTB-XL上，经过全微调后，其在九个和谐标签上的宏平均AUC达到96.90%。基于梯度的注意力图显示在与房间相关RVH相关的QRS电压和形态区域以及与LQTS相关的QRS到T/复极化间隔区域的显著性增加，与常规解释中常见的ECG区域一致。这些结果表明，成人规模的ECG预训练结合节律、形态和ST-T复极化语义描述在标签稀缺的情况下提高了可转移的儿童诊断，同时保持了临床可解释的波形焦点。
英文摘要：
Automated pediatric electrocardiogram (ECG) interpretation remains challenging because developmental differences in heart rate, intervals, and waveforms limit the transferability of models trained mainly on adult data, while expert-labeled pediatric ECG cohorts are scarce. We propose PEACE (Pediatric-Adult ECG Alignment via Cross-modal Enhancement), an adult-to-pediatric ECG transfer framework pretrained on MIMIC-IV ECGs and adapted to pediatric targets. PEACE integrates label-specific bidirectional contrastive learning (LSBC) to align ECG representations with diagnostic semantics and curriculum adaptive fusion (CAF) to stabilize optimization under limited pediatric supervision. Label-conditioned short text descriptors provide auxiliary semantic supervision during training, whereas inference requires ECG signals only. On ZZU-pECG, PEACE achieves macro-average AUCs of 59.39%, 81.74%, and 91.56% under zero-shot, 50-shot, and full fine-tuning settings, respectively, outperforming ECG-only, multimodal, and generic domain adaptation baselines including DANN and MMD. On PTB-XL, it reaches 96.90% macro-average AUC after full fine-tuning over nine harmonized labels with nonzero mapped incidence. Gradient-based attention maps show increased saliency around QRS voltage and morphology regions for chamber-related RVH and around QRS-to-T/repolarization intervals for LQTS, broadly consistent with ECG regions commonly inspected during routine interpretation. These results suggest that adult-scale ECG pretraining coupled with rhythm, morphology, and ST-T repolarization semantic descriptors improves transferable pediatric diagnosis under label scarcity while preserving clinically interpretable waveform focus.
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