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WSI Based DL for Diagnosing the IASLC Grading System of Lung Adenocarcinoma

NCT05925764 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 200

Last updated 2024-10-21

No results posted yet for this study

Summary

The purpose of this study is to evaluate the performance of a whole slide image based deep learning model for diagnosing the IASLC grading system in resected lung adenocarcinoma based on a multicenter prospective cohort.

Conditions

Interventions

DIAGNOSTIC_TEST

Whole Slide Image based Deep Learning

Whole Slide Image Based Deep Learning for Diagnosing the IASLC Grading System of Lung Adenocarcinoma

Sponsors & Collaborators

  • Shanghai Pulmonary Hospital, Shanghai, China

    lead OTHER

Eligibility

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

Timeline & Regulatory

Start
2024-10-15
Primary Completion
2024-12-31
Completion
2024-12-31

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 NCT05925764 on ClinicalTrials.gov