Meta 用 Muse Spark 1.3 辅助医学研究，产出 10 篇论文
Meta 用 Muse 模型和 500 万份病历辅助医学研究，已放出 10 篇论文，做医学+AI 交叉研究的可以看看流程设计。
Meta 构建了一套人类主导的研究框架，由 Muse Spark 1.3 和 Muse Wonder 驱动，可访问 500 万份去标识化的回顾性电子健康记录。一批医学专家用该系统开展原始研究，覆盖假设生成、代码执行和论文起草，科学决策权仍由研究者掌握。Meta 已公开这套流程产出的 10 篇论文，覆盖心脏病学、肿瘤学、传染病和急诊医学等领域。团队强调健康数据科学依赖不完美的真实世界数据，队列选择、变量和因果假设等关键环节仍需人工把关。
We’re exploring how AI can accelerate health science research. While AI has made significant breakthroughs in formal sciences like mathematics, health data science depends on imperfect real-world data and consequential choices about cohorts, variables, and causal assumptions. To explore how AI can assist health researchers, we built a human-led research scaffold powered by Muse Spark 1.3 and Muse Wonder with access to 5M retrospective de-identified electronic health records and publicly available data. A cohort of medical experts used the system to conduct original research, accelerate hypothesis generation, code execution, and manuscript drafting while maintaining full authority over scientific decisions. Today, we’re sharing 10 research manuscripts produced through this exploration, spanning cardiology, oncology, infectious disease, emergency medicine, and more. Read more in our research blog: go.meta.me/3U06wvD Your browser does not support the video tag. 🔗 View on Twitter 💬 8 🔄 7 ❤️ 51 👀 5844 📊 17 ⚡
