AI-Powered symptom watch aims to keep head and neck cancer patients out of the ER
NCT ID NCT05338905
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study tests whether using machine learning to closely monitor symptoms can help head and neck cancer patients avoid urgent hospital visits during radiation therapy. Researchers will compare intensive symptom tracking plus standard care to standard care alone in 72 patients with non-metastatic head and neck cancer. The goal is to see if early detection of worsening symptoms leads to better quality of life and fewer emergency visits.
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
- Active substance
- Intensive symptom surveillance with machine learning risk stratification
- What this could lead to
- If successful, this approach could help doctors catch worsening symptoms earlier and reduce the need for emergency hospital visits during radiation therapy.
- What could go wrong
- This is a small, early-stage study (72 participants) focused on non-metastatic disease, so results may not apply to all head and neck cancer patients. The intervention is observational and does not test a new drug or treatment.
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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
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Roswell Park Cancer Institute
Buffalo, New York, 14263, United States
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