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Diagnostic Performance of Neural Network-Based Artificial Intelligent in Detecting Pulmonary Nodule on Chest CT

Diagnostic Performance of Neural Network-Based Artificial Intelligent in Detecting Pulmonary Nodule on Chest CT

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR1800016226
Enrollment
Unknown
Registered
2018-05-21
Start date
2018-08-01
Completion date
Unknown
Last updated
2018-05-28

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

pulmonary nodules

Interventions

Gold Standard:Three sub-division radiologists with 15-20 years of diagnostic experience separately rated all CT images without time limitation.Pulmonary nodules confirmed by at least 2 radiologist wer
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Sponsors

Zhejiang Provincial People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. The chest LDCT scan was performed on the patients with physical examination, and the thickness was 1.25-1.5mm thick; 2. Scanning specifications and clear images; 3. The nodule diameter is 3cm and below.

Exclusion criteria

Exclusion criteria: 1. Patients with basic lung diseases: after chest surgery, large area of lung infection, large amount of chest water, diffuse interstitial pneumonia, etc.; 2. Poor quality of image collection; 3. The diameter of the substantial lesion in the lung is greater than 3cm; 4. The number of pulmonary nodules is greater than 20.

Design outcomes

Primary

MeasureTime frame
Pulmonary nodules;SEN, SPE, ACC, AUC of ROC;

Countries

China

Contacts

Public ContactXiangyang GONG

Zhejiang Provincial People's Hospital

cjr.gxy@hotmail.com+86 13958159183

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026