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NCT07280559

Evaluation of AI-assisted LDCT Screening in Lung Cancer

Not yet recruiting NA Last updated 12 December 2025
What this trial tests

NA trial testing AI-assisted Low-Dose CT Interpretation in Lung Cancer in 1,120 participants. Not yet recruiting.

Timeline
11 December 2025
Primary endpoint
31 December 2027
31 December 2031

Quick facts

Lead sponsorTaipei Veterans General Hospital, Taiwan
PhaseNA
StatusNot yet recruiting
Study typeINTERVENTIONAL
Allocationrandomized
Designparallel
Maskingsingle
Primary purposescreening
Enrollment1,120
Start date11 December 2025
Primary completion31 December 2027
Estimated completion31 December 2031
Sites1 location across Taiwan

Drugs / interventions tested

Conditions studied

Sponsor

Taipei Veterans General Hospital, Taiwan

Who can join

Adults 40 to 74, any sex, with Lung Cancer. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

This multicenter pragmatic randomized controlled trial evaluates whether AI-assisted interpretation of low-dose CT (LDCT) improves lung cancer screening performance compared with standard reading. Eligible participants are randomized to AI-assisted or conventional interpretation. The study assesses diagnostic accuracy, efficiency, lung cancer incidence, mortality, recurrence, and smoking cessation outcomes. Results will inform the clinical utility and potential implementation of AI-assisted LDCT in routine screening practice.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Lung Cancer

Currently open trials in the same condition.

Other Taipei Veterans General Hospital, Taiwan trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT07280559.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing