AI could spot lung cancer in Non-Smokers with family history
NCT ID NCT06295497
First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time
Summary
This study is testing whether an artificial intelligence program can help detect lung cancer early in non-smokers aged 50 to 75 who have a close family member with lung cancer. About 3,000 participants will get a low-dose CT scan of their chest, and the AI will analyze the images for suspicious nodules. If the AI finds a nodule, doctors will follow up to check if it is cancer. The goal is to see if AI can make lung cancer screening practical and accurate for this high-risk group.
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 software (Lung-SIGHT) to analyze low-dose CT scans
What this could lead to
If successful, this could provide a practical, AI-driven screening method to detect lung cancer early in non-smokers with a family history, potentially saving lives through earlier treatment.
What could go wrong
This is an early feasibility study with no control group, so results may not prove the AI is better than standard care. The AI might miss some cancers or flag too many false alarms, leading to unnecessary procedures.
Disclaimer
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the original study
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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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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
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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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Department of Clinical Oncology, Prince of Wales Hospital
RECRUITINGHong Kong, Hong Kong
Contact Phone: •••-•••-•••• Email: •••••@•••••
Contact Phone: •••-•••-•••• Email: •••••@•••••