Deep Learning Model for Pure Solid Nodules Classification
NCT ID: NCT05542992
Last Updated: 2022-09-16
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
260 participants
OBSERVATIONAL
2022-01-01
2023-12-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Interventions
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CT-based deep learning model
CT-based deep learning model for pure-solid nodules classifications
Eligibility Criteria
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Inclusion Criteria
* The maximum short-axis diameter of lymph nodes less than 3 cm on CT scan;
* Age ranging from 18-75 years;
* definied pathological examination report available;
* Obtained written informed consent.
Exclusion Criteria
* Poor quality of CT images;
* Participants with incomplete clinical information;
* Participants who have received neoadjuvant therapy before initial CT evaluation.
18 Years
75 Years
ALL
No
Sponsors
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Ningbo No.2 Hospital
OTHER
Zunyi Medical College
OTHER
The First Affiliated Hospital of Nanchang University
OTHER
The First Hospital of Lanzhou University, Gansu, China
UNKNOWN
Chang Chen
OTHER
Responsible Party
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Chang Chen
Professor
Locations
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Shanghai Pulmonary Hospital
Yangpu, Shanghai Municipality, China
Lanzhou
China, Gansu, , China
Zunyi
China, Guizhou, , China
Nanchang
China, Jiangxi, , China
Ningbo
China, Zhejiang, , China
Countries
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Facility Contacts
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Other Identifiers
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L21-022
Identifier Type: -
Identifier Source: org_study_id
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