AI eye on lung cancer: new study tests smart screening for High-Risk families
NCT ID NCT07600801
First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time
Summary
This study will enroll 2,250 adults with a family history of lung cancer to see if an AI model called Sybil can accurately predict future lung cancer from chest CT scans. Participants will provide previously taken CT images, and the AI will analyze them to estimate risk. The goal is to improve early detection in 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
CT scan and Sybil AI model
What this could lead to
If successful, this could lead to a more accurate, AI-based screening tool to catch lung cancer earlier in high-risk individuals.
What could go wrong
This is an early-stage study (not yet recruiting) that only tests the AI's prediction accuracy, not whether it improves health outcomes. The AI may not work as well in this specific group.
Disclaimer
Read more
Show less
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.
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.
Get updates
Get notified about this study
Sign up to get updates when this study changes or when new studies for FAMILY HISTORY OF LUNG CANCER are added.
By submitting, you agree to our Terms of 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.
Contacts and locations
Show contact details
Enter your email to view the contact information for this study.
By submitting, you agree to our Terms of use
Study contacts
-
Contact
Phone: •••-•••-•••• Email: •••••@•••••
Locations
-
Massachusetts General Hospital
Boston, Massachusetts, 02114, United States
Contact Phone: •••-•••-•••• Email: •••••@•••••