Meta 用 AI 辅助医学专家产出 10 篇研究稿件，覆盖心脏病学与肿瘤学等

摘要

Meta 表示其构建了一套由人类主导的研究框架，由 Muse Spark 1.3 与 Muse Wonder 驱动，可访问 500 万份回顾性去标识电子健康记录及公开数据。一组医学专家用该系统开展原创研究，在假设生成、代码执行和稿件撰写上提速，同时保留对科学决策的全部决定权。Meta 此次公开了由此产出的 10 篇研究稿件，涵盖心脏病学、肿瘤学、传染病、急诊医学等方向，详情见其研究博客。

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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: https://go.meta.me/3U06wvD

We’re exploring how AI can accelerate health science research.

摘要

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