A multicentric, real-world clinical study in China on the accuracy and application value of deep learning based artificial intelligence in the diagnosis of pulmonary nodules.

Status

Active, not recruiting

Phases

Early Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2000030379

Enrollment

Unknown

Registered

2020-02-29

Start date

2020-03-10

Completion date

Unknown

Last updated

2020-03-02

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

Conditions

Lung cancer

Interventions

Gold Standard:Histopathological examination

Index test:Artificial&#32

intelligence&#32

software

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Clinical imaging and CT examination revealed the presence of pulmonary nodules; 2. Be over or equal to 18 years old; 3. CT images showed that the diameter of pulmonary nodules was less than or equal to 30mm; 4. Cases with definite pathological diagnosis by operation or biopsy; 5. Pathological diagnosis which is not metastatic lung cancer; 6. CT screening showed at least one measurable pulmonary nodule; 7. Medical history such as smoking history and tumor history can be collected to calculate the predicted value of Mayo model. 8. DICOM format of lung CT can be provided. CT scanning layer thickness is <= 5mm.

Exclusion criteria

Exclusion criteria: 1. Lack, incomplete of previous imaging data; 2. Other conditions considered inappropriate for inclusion by the researchers.

Design outcomes

Primary

Measure	Time frame
Probability of malignancy assessed by AI technology ;SEN, SPE, ACC, AUC of ROC;	—

Countries

China

Contacts

Public ContactTao Xu

Affiliated Hospital of Qingdao University

xutao1008@163.com+86 18661802057

Outcome results

None listed

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