技术洞察 · ReHealth AI

预防医疗的技术底座
我们写清楚

联邦学习、因果归因、时序健康记忆——不是名词堆砌，是我们真正在做的事。读懂它们，才能理解预防医疗为什么可以被结算。

Technical Insights · ReHealth AI

The Technology Behind
Preventive Medicine

Federated learning, causal attribution, temporal health memory — not buzzwords. These are what we actually build. Understanding them is key to understanding why prevention can finally be billed.

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联邦学习 · 深度解析
联邦学习在医疗中的应用：数据不出院，模型持续进化
医院的患者数据为什么不能共享？联邦学习如何让分散在全国各地的医院数据协同训练心脑血管风险模型，同时保证患者隐私绝对安全？从技术原理到工程实践，完整解析。
2026-03-21 · 睿禾健康技术团队 12 分钟阅读 →
Federated Learning · Deep Dive
Federated Learning in Healthcare: Data Stays Local, Models Keep Evolving
Why can't hospitals share patient data? How does federated learning enable distributed hospitals to collaboratively train cardiovascular risk models while keeping patient data within hospital walls? Complete technical breakdown.
2026-03-21 · ReHealth AI Team 12 min read →
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预防医疗 · 行业分析
预防医疗决策：为什么70%的心脑血管支出本可避免
不是预防没价值，而是"预防结果无法被结算"。这句话背后是一个系统性困境，也是 ReHealth AI 存在的根本原因。
2026-03-21 10 分钟 →
Preventive Medicine · Analysis
Why 70% of Cardiovascular Costs Are Avoidable
Prevention has value. It just can't be billed. Behind this sentence lies a systemic failure — and the fundamental reason ReHealth AI exists.
2026-03-21 10 min →
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因果归因 · 技术原理
从"预测"到"证明有效"：PSM因果归因分析在医疗AI中的核心作用
大多数医疗AI只做预测。证明干预真的有效需要因果归因分析。PSM如何成为预防结算的关键证据？
2026-03-21 14 分钟 →
Causal Attribution · Technical
From "Prediction" to "Proof": Causal Attribution's Role in Healthcare AI
Most healthcare AI only predicts. Proving interventions actually work requires causal attribution. How does PSM become the key evidence for prevention settlement?
2026-03-21 14 min →