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Development and validation of a machine learning model for predicting the preoperative pulmonary function of lung nodule patients on the basis of computed tomography radiomics

Development and validation of a machine learning model for predicting the preoperative pulmonary function of lung nodule patients on the basis of computed tomography radiomics

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500110966
Enrollment
Unknown
Registered
2025-10-23
Start date
2025-11-01
Completion date
Unknown
Last updated
2025-10-27

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

Conditions

Lung cancer

Interventions

Observation group:NA

Sponsors

The Second People's Hospital of Guiyang
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Patients with pulmonary nodules; 2. Preoperative pulmonary function tests and chest CT examinations were conducted.

Exclusion criteria

Exclusion criteria: 1.No complete data for pulmonary function measurement 2. Severe artifacts or poor image quality in CT images.

Design outcomes

Primary

MeasureTime frame
Chest CT indicators;Pulmonary function parameters ;—

Countries

China

Contacts

Public ContactZheyuan Fan

The Second People's Hospital of Guiyang

zheyuan_fan@126.com+86 189 8556 1009

Outcome results

None listed

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