AI reads cancer slides: could it spot hidden spread?
NCT ID NCT06517979
First seen Dec 01, 2025 · Last updated Jun 23, 2026 · Updated 26 times
Summary
This study is developing an artificial intelligence (AI) model to detect whether cancer has spread to lymph nodes by analyzing digital images of tissue slides. Researchers will compare the AI's accuracy to that of pathologists in 10,000 cancer patients. The goal is to see if AI can help make lymph node diagnosis faster and more reliable in everyday clinical practice.
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Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
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Contacts and locations
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Study contacts
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Contact
Phone: •••-•••-•••• Email: •••••@•••••
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Contact
Phone: •••-•••-•••• Email: •••••@•••••
Locations
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Sun Yat-sen Memorial Hospital of Sun Yat-sen University
RECRUITINGGuangzhou, Guangdong, 510120, China
Contact Phone: •••-•••-•••• Email: •••••@•••••
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
Active substance
Artificial intelligence (AI)-based diagnostic model
What this could lead to
If successful, this AI tool could help pathologists detect cancer spread to lymph nodes faster and more accurately, potentially improving treatment decisions.
What could go wrong
This is a diagnostic study, not a treatment. The AI model may not perform as well in real-world settings as in lab tests, and it requires further validation before routine use.
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.