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Development and Validation of a Deep Learning System for Nasopharyngeal Carcinoma Using Endoscopic Images

NCT05627310 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 50000

Last updated 2022-11-25

No results posted yet for this study

Summary

Develop a deep learning algorithm via nasal endoscopic images from eight NPC treatment centerto detect and screen nasopharyngeal carcinoma(NPC).

Conditions

  • Nasopharyngeal Carcinoma

Interventions

OTHER

Diagnostic

Training dataset was used to train the deep learning model, which was validated and tested by external dataset.

Sponsors & Collaborators

  • Xiangya Hospital of Central South University

    collaborator OTHER

  • The First Affiliated Hospital of Nanchang University

    collaborator OTHER

  • Fujian Medical University Union Hospital

    collaborator OTHER

  • Quan Zhou First Affiliated Hospital of Fujian Medical University

    collaborator UNKNOWN

  • First Affiliated Hospital of Guangxi Medical University

    collaborator OTHER

  • People's Hospital of Guangxi Zhuang Autonomous Region

    collaborator OTHER

  • The People' s Hospital of Jiangmen

    collaborator UNKNOWN

  • Eye & ENT Hospital of Fudan University

    lead OTHER

Principal Investigators

  • Hongmeng Yu, MD PhD · Eye&ENT Hospital, Fudan University

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-11-01
Primary Completion
2023-12-31
Completion
2024-03-31

Countries

  • China

Study Locations

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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 NCT05627310 on ClinicalTrials.gov