AI reads faces to predict delirium before it strikes
NCT ID NCT07337356
First seen Jun 24, 2026 · Last updated Jun 27, 2026 · Updated 1 time
Summary
Delirium is common in hospital intensive care units (ICUs) and can be hard to diagnose. This study will use non-contact cameras to analyze patients' facial micro-expressions and other biological signals. By combining this data with machine learning, researchers aim to build a model that predicts delirium early. The study plans to enroll 795 adult ICU patients at Ruijin Hospital.
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
- What this could lead to
- If successful, this could lead to a tool that helps doctors spot delirium earlier and more accurately in ICU patients, potentially improving outcomes.
- What could go wrong
- This is an early-stage observational study, not a treatment trial. The model may not be accurate enough for real-world use, and results may not apply to all patients.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
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