CI

At a glance

ClinicalIndex Comparison Record
N/ACompleted· 296 enrolled
Drug / intervention
radiologists reference AI reportsother
Likely dose
Not stated in record
Structured eligibility isn't available for this trial yet — see the full criteria in the Eligibility tab below.

Standardized by ClinicalIndex from the ClinicalTrials.gov record · verify against the source.

Search/NCT07117266
NCT07117266N/ACompleted

A DeepSeek-Powered AI System for Automated Chest Radiograph Interpretation in Clinical Practice

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology·interventional·Posted Aug 12, 2025·Updated Sep 12, 2025

In Brief

A clinical study evaluating radiologists reference AI reports for X-Ray and 2 related conditions. Completed, enrolled 296 participants across 3 sites.

Detailed Summary

There's a global shortage of radiologists. Radiology AI's automatic reporting is key for boosting efficiency and meeting patient needs, especially in resource-poor areas. Multimodal large models enable medical image auto-reporting systems. ChatGPT 4o can diagnose medical images but has issues like being closed-source and "hallucinations." The new open-source Janus Pro 1B-with strong performance, "any-to-any" capability, low cost, and open access-shows potential for medical imaging tasks with training. But little research explores its use here; most models are general, lacking field-specific optimization and systematic evaluation. This study will develop Janus Pro 1B-CXR (a medical image-specific model) via public data, test its value in diagnosis and reporting, and build an efficient automated system.

Study Details

Timeline

N/ACompletedFinished
2026
First PostedAug 12, 2025
Enrollment StartAug 1, 2025
Primary CompletionAug 12, 2025
TodayJul 2, 2026
Enrollment to primary: 11 daysPosted 11 months ago

Interventions

radiologists reference AI reportsother

Radiologists generate reports with reference to AI reports