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A study of large model algorithms for artificial intelligence targeting respiratory interventions based on lung CT

A study of large model algorithms for artificial intelligence targeting respiratory interventions based on lung CT

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400093423
Enrollment
Unknown
Registered
2024-12-04
Start date
2024-03-11
Completion date
Unknown
Last updated
2024-12-09

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

Conditions

pulmonary nodule

Interventions

Trail group:NA

Sponsors

The Fourth Affiliated Hospital of Soochow University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: (1) People whose layer thickness is not greater than 1.0 mm and who are diagnosed with small nodular lung lesions on chest CT; (2) People who need bronchoscopy for peripheral lung lesions detected by chest CT; (3) Signed informed consent; (4) Being not less than 18 years old;

Exclusion criteria

Exclusion criteria: (1) Patients deemed unsuitable by the investigator to participate in this trial. (2) Chest CT noise fields affecting the labeling of the pulmonary airway tree (3) Patients who refused to sign the informed consent form

Design outcomes

Primary

MeasureTime frame
Nodule detection: automatic detection of nodule lesion areas; and;

Countries

China

Contacts

Public ContactJunhong Jiang

The Fourth Affiliated Hospital of Soochow University

Jiang20001969@163.com+86 138 1267 3528

Outcome results

None listed

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