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Deep Learning Model for Pure Solid Nodules Classification

NCT05542992 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 260

Last updated 2022-09-16

No results posted yet for this study

Summary

The purpose of this study is to compare the predictive performance of a CT-based deep learning model for pure-solid nodules classification and compared with the tumor maximum standardized uptake value on PET in a multicenter prospective cohort.

Conditions

Interventions

DIAGNOSTIC_TEST

CT-based deep learning model

CT-based deep learning model for pure-solid nodules classifications

Sponsors & Collaborators

  • Ningbo No.2 Hospital

    collaborator OTHER

  • Zunyi Medical College

    collaborator OTHER

  • The First Affiliated Hospital of Nanchang University

    collaborator OTHER

  • The First Hospital of Lanzhou University, Gansu, China

    collaborator UNKNOWN

  • Chang Chen

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-01-01
Primary Completion
2023-12-31
Completion
2023-12-31

Countries

  • China

Study Locations

More Related Trials

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 NCT05542992 on ClinicalTrials.gov