Tundra Space

Tundra Space

Clinical Research Directory

Browse clinical research sites, groups, and studies.

Back to Studies
NOT YET RECRUITING
NCT07110259
NA

AI-Based DeepGEM Tool for Predicting Gene Mutations in NSCLC Patients: A Randomized Controlled Study

Sponsor: Jianxing He

View on ClinicalTrials.gov

Summary

This prospective, multicenter, randomized controlled trial aims to evaluate the clinical utility of DeepGEM, an artificial intelligence (AI)-based mutation prediction tool based on histopathological whole-slide images, in patients with non-small cell lung cancer (NSCLC). The study will assess whether DeepGEM can facilitate molecular testing, increase targeted therapy utilization, and improve survival outcomes in a real-world clinical setting. Patients with stage II-IV treatment-naïve NSCLC and qualified pathology slides for DeepGEM analysis will be enrolled. Eligible participants with AI-predicted EGFR, ALK, or ROS1 mutations will be randomized in a 4:1 ratio to either the DeepGEM-informed group (clinicians can access AI results to guide further testing and treatment) or the standard care group (clinicians are blinded to AI results and follow routine care).

Official title: Application of the Artificial Intelligence-Based Gene Mutation Prediction Tool DeepGEM in Patients With Non-Small Cell Lung Cancer (NSCLC): A Prospective, Multicenter, Randomized Controlled Trial

Key Details

Gender

All

Age Range

18 Years - 75 Years

Study Type

INTERVENTIONAL

Enrollment

950

Start Date

2025-07-31

Completion Date

2028-07-31

Last Updated

2025-08-07

Healthy Volunteers

No

Interventions

OTHER

DeepGEM-guided Molecular Testing and Treatment

Artificial intelligence-based mutation prediction using DeepGEM to guide clinical decision-making for molecular testing and therapy selection.

OTHER

Standard Diagnostic Pathway

DeepGEM is used for eligibility screening, but its results are withheld. Clinicians manage patients per standard diagnostic and treatment practices.