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An artificial intelligence lung nodule indentification software based on CT medical imaging

An artificial intelligence lung nodule indentification software based on CT medical imaging

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200061984
Enrollment
Unknown
Registered
2022-07-15
Start date
2022-07-20
Completion date
Unknown
Last updated
2023-04-03

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:Chest CT images, imaging reports, and pathology results.
Index test:Artificial&#32
intelligence&#32
pulmonary&#32
nodule&#32
automatic&#32
identification&#32
software

Sponsors

Shandong Cancer Institute
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Chest CT image data of patients who are greater than or equal to 18 years old and have pulmonary nodules greater than or equal to 4 mm found by imaging; 2. Some chest CT image data without nodules, including lung diseases such as pneumonia and emphysema, and chest CT image data without obvious abnormalities; 3. The CT data image is a DICOM format image with a slice thickness range of 0.625-2 mm.

Exclusion criteria

Exclusion criteria: CT image data image slice thickness of 5 mm or more.

Design outcomes

Primary

MeasureTime frame
pulmonary nodules;sensitivity;specificity;accuracy;Kappa coefficient;—

Countries

China

Contacts

Public ContactYong Huang

Zhuhai Hengqin Shengao Yunzhi Technology Co., Ltd.

huangyong1970888@sina.com+86 15865280280

Outcome results

None listed

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