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AI-based multimodal medical information fusion system for decision support in Lung cancer

AI-based multimodal medical information fusion system for decision support in Lung cancer

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600125070
Enrollment
Unknown
Registered
2026-05-21
Start date
2026-06-01
Completion date
Unknown
Last updated
2026-05-25

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

Conditions

Pulmonary nodules (diameter < 30 mm)

Interventions

Index test:1.Automatic pulmonary nodule detection and localization model 2.Pulmonary nodule volume doubling time (VDT) prediction model 3.Benign vs malignant classification and adenocarcinoma invasive

Sponsors

Beijing Cancer Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. It has thin-layer complete chest CT images in the plain scan period; 2. Pulmonary nodules with a clear surgical or puncture pathological diagnosis; 3. The average diameter of the maximum cross-section of the lesion is less than or equal to 30cm; 4. The scanning instruments are all four CTS from Peking University Cancer Hospital, including Philips Brilliance 64-slice iCT, GE Revolution CT and Discovery Spectral CT.

Exclusion criteria

Exclusion criteria: 1. The image scanning range is incomplete. 2. Poor image quality affects interpretation, such as :(1) Improper positioning; (2) Obvious imaging artifacts; (3) Excessive noise, etc. 3. The researchers consider it inappropriate to include it in this clinical trial.

Design outcomes

Primary

MeasureTime frame
Sensitivity;Specificity;Accuracy;

Countries

China

Contacts

Public ContactMa Shaohua

Peking University Cancer Hospital & Institute, Beijing

doctor_msh@bjmu.edu.cn+86 10 8812 1122

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 30, 2026