Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH
This study demonstrates that ML models using age, ADA, and LDH can effectively classify the etiologies of pleural effusion, suggesting that ML-based approaches may enhance diagnostic decision-making.
Authors
- Ming‐Ming Shao
- Qingyu Chen (ORCID: https://orcid.org/0000-0002-6036-1516)
- Feng‐Shuang Yi (ORCID: https://orcid.org/0000-0003-2822-5618)
- Huan‐Zhong Shi (ORCID: https://orcid.org/0000-0002-1154-7920)
- Shumin Yin
Institutions
- Capital Medical University (CN)
- Beijing Chao-Yang Hospital, Capital Medical University (CN)
Publication Details
- Journal
- Respiratory Research
- Published
- 2025-05-02
- DOI
- https://doi.org/10.1186/s12931-025-03253-2
- Citations
- 4
- Primary Topic
- Pleural and Pulmonary Diseases
- Type
- article
- Field-Weighted Citation Impact
- 6.07
Funders
- National Natural Science Foundation of China