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Artificial intelligence techniques for automatic generation of chest X-ray image reports

Artificial intelligence techniques for automatic generation of chest X-ray image reports

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400088131
Enrollment
Unknown
Registered
2024-08-12
Start date
2024-08-31
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

pneumonia

Interventions

chest X-ray group:none

Sponsors

Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
1 Years to 99 Years

Inclusion criteria

Inclusion criteria: All patients at Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University between 1 January 2022 and 31 December 2023 who require chest X-ray examination due to clinical suspicion of cardiothoracic disease or other reasons.

Exclusion criteria

Exclusion criteria: (1) Those whose chest X-ray image quality does not satisfy the diagnosis. (2) Chest X-ray results do not contain one of the following diseases: pneumonia, bronchitis, pulmonary oedema, pneumothorax, pleural effusion

Design outcomes

Primary

MeasureTime frame
Pneumothorax volume;Volume of pleural effusion;Severity of pneumonia;Severity of pulmonary edema;—

Countries

China

Contacts

Public ContactYang Qihua

Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University

yangqih2@mail.sysu.edu.cn+86 180 0229 9992

Outcome results

None listed

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