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An Interpretable Fundus Diseases Report Generating System Based On Weakly Labelings

NCT06918028 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 9999

Last updated 2025-04-09

No results posted yet for this study

Summary

To establish a multimodal fundus image report generation model to realize an interpretable system for multiple fundus diseases, multimodal image analysis, diagnosis, and treatment decision automatic reporting based on weakly labeled training data. Construct an interpretable feature fusion network for the clinical and imaging features of fundus lesions, and we hope to extract new imaging markers that can predict the occurrence and progression of various fundus lesions at an early stage, and ultimately verify them in real clinical data, further providing possible directions for exploring the molecular mechanisms of refractory fundus lesions, and may also provide new ideas for the precise prevention and treatment of fundus lesions.

Conditions

Interventions

OTHER

With fundus diseases

With fundus diseases

OTHER

Without fundus diseases

Without fundus diseases

Sponsors & Collaborators

  • Zhongshan Ophthalmic Center, Sun Yat-sen University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-05-31
Primary Completion
2025-12-31
Completion
2026-12-31

Countries

  • China

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06918028 on ClinicalTrials.gov