EligibleTrials

LUNG-07: Advancing Precision-Based Lung Cancer Screening: Implementation, AI-Guided Risk Stratification, and Biomarker Integration (CREST AI)

Recruiting · NCT07408531 · Interventional (participants receive a specific treatment) · Lead sponsor: University of Illinois at Chicago

View the official record on ClinicalTrials.gov →
Lung cancer

Interventions studied

Sybil Artificial Intelligence (AI) screening

What this trial is about

This research study aims to investigate methods for enhancing lung cancer screening. The study will investigate whether an artificial intelligence (AI) tool, known as Sybil, can aid in predicting the risk of lung cancer. The investigators will also examine whether expanding the screening criteria (based on the guidelines of the Potter and American Cancer Society (ACS)) can help identify individuals at risk who are not currently included in the U.S. Preventive Services Task Force (USPSTF) guidelines.

Who can take part

Age range
50 Years to 80 Years
Sex
All (male and female)
Healthy volunteers
Yes - healthy volunteers may be accepted
Phase
Not applicable (e.g. observational or device study)
Study type
Interventional (participants receive a specific treatment)

Inclusion criteria

Exclusion criteria

Where it is running

2 locations listed across 1 US state.

Read the full protocol, contacts and eligibility on ClinicalTrials.gov →

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