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Deep convolutional neural network model based on chest CT to predict the grading of chronic obstructive pulmonary disease and the risk of acute exacerbation

Deep convolutional neural network model based on chest CT to predict the grading of chronic obstructive pulmonary disease and the risk of acute exacerbation

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000035891
Enrollment
Unknown
Registered
2020-08-19
Start date
2020-10-01
Completion date
Unknown
Last updated
2020-08-24

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

Conditions

Chronic obstructive pulmonary disease

Interventions

Gold Standard:Clinical symptoms and lung function test results for chronic obstructive pulmonary disease
neural&#32
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DenseNet&#32
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Architecture

Sponsors

Shanghai General Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: Inclusion criteria for the case group: 1. Clinically confirmed COPD with symptoms and/or risk factors; 2. Lung function examination was performed within 3 days before and after CT examination, and pulmonary function examination was performed within the same day in case of acute exacerbation of COPD; 3. No treatment was performed between CT examination and lung function examination. Inclusion criteria for the normal group: 1. Previous medical history or this visit is not COPD or asthma; 2. A lung function test was performed within 1 week before and after the CT examination, and the lung function test results were normal.

Exclusion criteria

Exclusion criteria: Exclusion criteria for the case group: 1. The presence of diseases affecting pulmonary observation in CT images; 2. History of asthma attacks; 3. Post-treatment is difficult to reconstruct bronchus and lung parenchyma; 4. Lung function examination is not fully cooperative. Exclusion criteria for the normal group: 1. The presence of diseases affecting lung observation in CT images; 2. History of asthma attacks.

Design outcomes

Primary

MeasureTime frame
Prediction probability of convolutional neural network;

Countries

China

Contacts

Public ContactLin Zhang

Shanghai General Hospital

iceblue033@163.com+86 13917138036

Outcome results

None listed

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