A Cohort Study of Pediatric Severe Community-Acquired Pneumonia Involving AI-Based CT Image Parameters and Electronic Health Record Data
The use of AI-derived chest CT indices may achieve high diagnostic accuracy and guide precise interventions for patients with severe CAP. However, clinical, laboratory, and AI-derived chest CT indices should be included to accurately predict and treat severe CAP.
Authors
- Yuchen Wang (ORCID: https://orcid.org/0000-0002-0262-1869)
- Xin Nie (ORCID: https://orcid.org/0000-0001-6635-0327)
- Jianpeng Yuan
- A. Liu (ORCID: https://orcid.org/0009-0005-1090-1683)
- Li Wang (ORCID: https://orcid.org/0000-0002-2760-2891)
- Rui Pu (ORCID: https://orcid.org/0000-0003-3366-739X)
- Hongman Xue
- Junfeng Xie (ORCID: https://orcid.org/0000-0002-0669-5339)
- Mengyuan He
- Jing Yi (ORCID: https://orcid.org/0000-0002-8334-1825)
- W. Yu
Institutions
- Sun Yat-sen University (CN)
- The Seventh Affiliated Hospital of Sun Yat-sen University (CN)
Publication Details
- Journal
- Infectious Diseases and Therapy
- Published
- 2025-08-08
- DOI
- https://doi.org/10.1007/s40121-025-01197-0
- Citations
- 1
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Innovative Research Group Project of the National Natural Science Foundation of China