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D-Lung: An Analytics Platform for Lung Cancer Based on Deep Learning Technology

NCT04036903 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 130

Last updated 2023-02-08

No results posted yet for this study

Summary

Lung cancer is one of main cause of cancer death in worldwide, characterized of low 5-year survival rate of less than 20%. Pulmonary nodule is considered as the typical imaging manifestation in early stage of lung cancer. The National Lung Screen Trial has demonstrated that the mortality rates could decline greatly, by the utility of low-dose helical computed tomography for screen of pulmonary nodules. Thus, automatic detection, diagnosis and management of pulmonary nodules, play the vital roles in computer-aided lung cancer screening and early intervention.

Conditions

Interventions

RADIATION

computed tomography

thoracic CT examinations for diagnosis, and/or follow-up.

Sponsors & Collaborators

  • Department of Computer Science & Engineering, CUHK

    collaborator UNKNOWN

  • Chinese University of Hong Kong

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2018-07-01
Primary Completion
2020-06-30
Completion
2020-06-30

Countries

  • Hong Kong

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 NCT04036903 on ClinicalTrials.gov