RecruitingNCT07555002

Prospective User Study and Multicenter Validation of Multimodal Medical Imaging Large Models

Prospective User Study and Multicenter Validation of Multimodal Medical Imaging Large Models in the Diagnosis of Common Systemic Diseases


Sponsor

The Third Affiliated Hospital of Southern Medical University

Enrollment

1,000 participants

Start Date

Jan 1, 2026

Study Type

OBSERVATIONAL

Conditions

Summary

This study aims to evaluate the diagnostic performance and clinical utility of a multimodal medical imaging large model in identifying common systemic diseases. Through a retrospective reader study involving multiple centers, the research will compare the diagnostic accuracy, sensitivity, and specificity of radiologists with and without AI assistance. The goal is to validate the model's robustness and its impact on the diagnostic efficiency of clinicians across diverse healthcare settings.


Eligibility

Min Age: 18 Years

Inclusion Criteria3

  • Patients who underwent systemic medical imaging examinations (e.g., CT or MRI) at participating centers for common systemic diseases.
  • Imaging data must have a confirmed clinical reference standard, expert consensus, or pathological diagnosis.
  • Availability of complete DICOM format images with standard acquisition protocols.

Exclusion Criteria2

  • Poor image quality (e.g., severe motion or metal artifacts) that precludes definitive diagnosis.
  • Cases with incomplete clinical or pathological reference standards. Corrupted image files or duplicate cases.

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Interventions

OTHERStandalone Radiologist Interpretation

Radiologists interpret the medical images independently without any assistance from the AI model to establish a baseline performance.

OTHERAI-assisted Radiologist Interpretation

Radiologists interpret the same set of medical images with the assistance of the multimodal medical imaging large model to evaluate the improvement in diagnostic performance.


Locations(1)

The Third Affiliated Hospital of Southern Medical University

Guangzhou, Guangdong, China

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NCT07555002


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