跨医院罕见病诊断新框架，用隐状态通信保护隐私。
MedLatentDx: Latent Multi-Agent Communication for Cross-Hospital Rare-Disease Diagnosis
- 医院间不传文本，只传压缩的隐状态块进行协作诊断。
- 在跨机构基准上提升诊断准确率，同时降低临床内容泄露风险。
- 适用于不同模型医院，支持隐私保护下的多机构联合诊断。
罕见病影响全球超3亿患者，涉及7000多种疾病，但单个医院难以积累足够病例实现可靠诊断。跨医院协作可通过共享特定病例证据提升诊断能力，但隐私法规禁止可识别的临床文本跨机构传输。现有医疗代理系统依赖文本交换，而原始隐状态（如隐藏状态、键值缓存）仍可能暴露提示衍生的临床信息。本文提出MedLatentDx，一种基于隐状态的多代理通信框架：各医院代理本地保存临床记录与检索病例，仅向主代理发送紧凑的隐状态键值块以完成罕见病诊断。该框架支持两种部署模式：同架构医院采用隐状态蒸馏，异构模型医院则使用跨家族隐状态对齐。在自建的跨医院级罕见病基准CrossRare-Bench上，MedLatentDx在提升跨机构诊断性能的同时，显著降低了可重构的临床内容泄漏风险，优于原始隐状态通信基线。
原文摘要 · Abstract (English)
Rare diseases affect over $300$ million patients across more than $7{,}000$ conditions, yet no single hospital encounters enough cases of any one condition for reliable diagnosis. Cross-hospital collaboration could help by allowing a diagnosing institution to use distributed, case-specific diagnostic evidence, but privacy regulations restrict the transmission of identifiable clinical text across institutional boundaries. This setting raises two challenges: existing medical agent systems often rely on textual evidence exchange, while raw latent states such as hidden states and KV caches may still reveal prompt-derived clinical content. We introduce MedLatentDx, a latent multi-agent communication framework in which hospital agents keep private clinical records and retrieved cases local, and send compact latent KV blocks to a host agent for rare-disease diagnosis. MedLatentDx supports two deployment settings: same-backbone hospital agents use latent KV distillation, while hospitals with different LLM backbones use cross-family latent alignment. On CrossRare-Bench, a self-built large-scale rare-disease benchmark with hospital-level partitions, MedLatentDx improves cross-hospital diagnostic performance while reducing reconstructable clinical content relative to raw-latent communication baselines.
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