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Construction and application of an artificial intelligence-based diagnostic model for pulmonary fungal infections

Construction and application of an artificial intelligence-based diagnostic model for pulmonary fungal infections

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500111767
Enrollment
Unknown
Registered
2025-11-05
Start date
2025-11-07
Completion date
Unknown
Last updated
2025-11-11

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

Conditions

Pulmonary fungal infection

Interventions

Training and Validation group:None
Standalone Testing group:None

Sponsors

Wuxi People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Age: 18 - 85 years old, gender not restricted; 2. Patients diagnosed clinically (based on pathogenesis, imaging, clinical manifestations, etc.) as having pulmonary infections caused by one or more of Aspergillus, Candida, Pneumocystis, or Cryptococcus; 3. Patients have complete chest CT imaging data (meeting the requirements for diagnosis and model analysis); 4. Patients have relatively complete clinical history records, including but not limited to: past medical history, personal history, immune status, related symptoms and signs, blood routine, inflammatory markers, pathogen examination results (such as culture, smear, antigen/antibody detection, PCR, NGS, etc.); 5. Agree to use their clinical data in this retrospective study (if applicable, handle informed consent in accordance with the requirements of the ethics committee).

Exclusion criteria

Exclusion criteria: 1. The quality of CT images is poor and cannot meet the analysis requirements; 2. The clinical data is severely lacking, and key information cannot be obtained; 3. Other active pulmonary diseases that seriously affect the interpretation of pulmonary images (such as tuberculosis, lung cancer, etc.) are present, unless these diseases are specific stratification factors of the study; 4. Pregnant and lactating women (unless the study specifically focuses on such populations); 5. Other patients who the clinical doctors consider are not suitable to participate in this study.

Design outcomes

Primary

MeasureTime frame
Accuracy;Precision;

Secondary

MeasureTime frame
Recall / Sensitivity;Specificity;F1 Score;Area Under the ROC Curve;Confusion Matrix;

Countries

China

Contacts

Public ContactHaoda Yu

Wuxi People's Hospital

yhd9988@sina.com+86 138 1510 0509

Outcome results

None listed

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