AI predicts missed HIV appointments: could save lives?
NCT ID NCT06604663
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study tests whether machine learning can predict which HIV patients are likely to miss clinic visits or have treatment failure. Researchers will give clinic workers risk alerts to help them reach out to high-risk patients. The goal is to improve retention in care and viral suppression across 80,000 patients in Kenya.
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
- Active substance
- Clinical decision support system (CDSS) using machine learning algorithms
- What this could lead to
- If successful, this could help clinics in Africa identify patients at risk of missing appointments or failing treatment, improving HIV care and reducing viral spread.
- What could go wrong
- This is an observational study without a new drug or treatment. The algorithms may not work as well in real-world settings, and results may not apply to other regions.
This is an AI summary of the original study and may miss details. Read our disclaimer.
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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.
Contacts and locations
Locations
-
AMPATH
Eldoret, Kenya
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