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Application of automatic cough sound analysis based on artificial intelligence algorithm in the diagnosis of common respiratory diseases in children

Application of automatic cough sound analysis based on artificial intelligence algorithm in the diagnosis of common respiratory diseases in children

Status
Recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200056207
Enrollment
Unknown
Registered
2022-02-01
Start date
2022-01-20
Completion date
Unknown
Last updated
2024-08-19

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

Conditions

Iespiratory tract disease in children

Interventions

Laryngitis group:None
Bronchiolitis group:None
Acute asthma attack groups:None

Sponsors

Shanghai Children's Medical Center Affiliated to Shanghai Jiao Tong University School of Medicine
Lead Sponsor

Eligibility

Sex/Gender
All
Age
No minimum to 18 Years

Inclusion criteria

Inclusion criteria: 1. Aged > 28 days, <= 18 years, gender and age are not limited; 2. Clinical cough symptoms; 3. Within 7 days of the onset of the disease; 4. Admission diagnosis is consistent with one of the following diagnoses: laryngitis, capillary bronchitis, bronchitis, pneumonia or acute asthma attacks; 5. Sign an informed consent form.

Exclusion criteria

Exclusion criteria: 1. Receive mechanical ventilation or treatment with high nasal flow; 2. The presence of airway structural diseases including throat softening, trachea softening and bronchial malformation; 3. People with chronic lung disease, gas chest, congenital heart disease, immunodeficiency and treatment with long-term oral hormones or immunosuppressants; 4. Those who have undergone eye, chest or abdominal surgery in the last 3 months.

Design outcomes

Primary

MeasureTime frame
Cough sound data;

Countries

China

Contacts

Public ContactJing Zhang

Shanghai Children's Medical Center Affiliated to Shanghai Jiao Tong University School of Medicine

zhangjing_yq@163.com+86 21 38626161-87821

Outcome results

None listed

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