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2 clinical studies listed.
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Tundra lists 2 Pathology Foundation Model clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.
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NCT07408167
AI Models in Clinical Pathology Diagnosis: A Multicenter RCT
The investigators plan to conduct a multicenter, prospective, randomized controlled trial to systematically evaluate the incremental value of pathology-based artificial intelligence (AI) models in a pan-disease diagnostic workflow. The study will primarily compare interpretation using an AI-assisted platform with conventional independent slide reading in terms of diagnostic accuracy (e.g., AUC), reading efficiency (e.g., diagnostic time), diagnostic report quality, diagnostic confidence (Likert scale), and pathologists' satisfaction with the AI model. Investigators will also assess superiority among less experienced (junior) pathologists and non-inferiority among more experienced (senior) pathologists. Successful completion of this project will provide high-level prospective evidence to support standardized deployment, quality control, and broader implementation of pathology AI in clinical practice. This trial may also evaluate the potential benefits and risks of using AI tools in medical research.
Gender: All
Ages: 18 Years - 100 Years
Updated: 2026-02-13
3 states
NCT07291362
AI-Assisted Pathologist Performance Improvement: A Multicenter, Prospective, Randomized Controlled Trial
The investigators plan to conduct a multicenter, prospective, randomized controlled trial to systematically evaluate the added value of pathology-based AI models in the gastric cancer diagnostic workflow. The study will focus on comparing AI-assisted platform interpretation with conventional independent slide reading in terms of diagnostic accuracy (e.g., AUC), reading efficiency (e.g., comparison of time to diagnosis), quality of diagnostic reports, diagnostic confidence (Likert scale), and pathologists' satisfaction with the AI models. The investigators will also assess superiority for less-experienced (junior) pathologists and noninferiority for more-experienced (senior) pathologists. Successful completion of this project will provide high-level prospective evidence to support the standardized deployment, quality control, and broader application of pathology AI in the gastric cancer care pathway.
Gender: All
Ages: 18 Years - Any
Updated: 2026-02-10
2 states