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Research on an Auxiliary Diagnosis Model for Childhood Pneumonia Based on Clinical Thinking and Deep Learning

Research on an Auxiliary Diagnosis Model for Childhood Pneumonia Based on Clinical Thinking and Deep Learning

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500113231
Enrollment
Unknown
Registered
2025-11-26
Start date
2025-01-01
Completion date
Unknown
Last updated
2025-12-01

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

Conditions

Community acquired pneumonia in children

Interventions

Gold Standard:Organize two senior respiratory specialists (associate chief physician or above, with more than 10 years of relevant work experience) to review the diagnosis of pneumonia. If the two exp
Index test:Deep learning assisted diagnostic model

Sponsors

Fujian Children's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
No minimum to 18 Years

Inclusion criteria

Inclusion criteria: 1. Age range: from birth to 18 years inclusive, no gender restrictions; 2. Paediatric patients shall undergo a chest X-ray in the frontal position prior to hospital admission; 3. X-ray images must be clear.

Exclusion criteria

Exclusion criteria: 1. The patient had no chest X-ray images taken prior to hospital admission; 2. Chest X-ray images were of poor quality, exhibiting artefacts, metallic foreign bodies, etc.; 3. The patient was diagnosed with neonatal pneumonia, hospital-acquired pneumonia, pulmonary tuberculosis, lung tumours, or other pulmonary diseases.

Design outcomes

Primary

MeasureTime frame
Precision;Recall;F1 score;

Countries

China

Contacts

Public ContactRao Yanying

Fujian Children's Hospital

raoyanying@fjmu.edu.cn+86 158 8016 7125

Outcome results

None listed

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