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An AI tool for prioritizing candidate biomarkers from wearable sensor data
Our short summary of Google’s engineering write-up. The full story, with all the detail, is on their blog.
Read the full write-up on research.google (opens in a new tab)Problem
Users needed trustworthy biomarkers from wearable data, but existing tools missed statistical rigor.
Solution
They built a multi‑agent system that iteratively generates hypotheses, runs statistical tests, trains models, and checks literature to rank biomarkers, all under human supervision.
Recovered known signals, found new convergent biomarkers, and boosted prediction accuracy
Want the architecture, code and numbers? They’re in the original post.
Read the full write-up on research.google (opens in a new tab)
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