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Construction of Clinical Prognosis Model and Time Series CT Image Prediction Model for IPF (Idiopathic Pulmonary Fibrosis) Based on Machine Learning

Construction of Clinical Prognosis Model and Time Series CT Image Prediction Model for IPF (Idiopathic Pulmonary Fibrosis) Based on Machine Learning

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400083089
Enrollment
Unknown
Registered
2024-04-15
Start date
2024-04-15
Completion date
Unknown
Last updated
2024-04-22

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

Conditions

Idiopathic pulmonary fibrosis

Interventions

None:None

Sponsors

Shanghai Chest Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 85 Years

Inclusion criteria

Inclusion criteria: 1)Subjects were diagnosed with IPF from January 2018 to November 2022 2)Subjects aged >18 when first diagnosed with IPF 3)Subjects have corresponding High Resolution CT(HRCT), slice thickness = 3mm 4)Subjects conform to either usual interstitial pneumonia (UIP) or probable UIP patterns in HRCT

Exclusion criteria

Exclusion criteria: 1)Subjects were diagnosed with known etiology, such as connective tissue disease, chronic hypersensitivity pneumonitis, smoke-related interstitial lung disease, sarcoidosis, pneumoconiosis, asbestos lung, and Langerhans cell histiocytosis 2)If the subject conforms to antinuclear antibody (ANA) is a nucleolar pattern or centromere pattern positive 3)Subjects have risk factors exposure such as occupational exposure 4)Subjects’ HRCT is too vague to analyze 5)Subjects combined with infection at baseline and the fibrotic lesions were cured soon after treatment

Design outcomes

Primary

MeasureTime frame
receiver operating characteristic curve (ROC);survival status;

Secondary

MeasureTime frame
survival time;C-index;

Countries

China

Contacts

Public ContactFeng Li

Shanghai Chest Hosptial

lifeng741@aliyun.com+86 137 6130 6949

Outcome results

None listed

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