Developing machine learning‐driven acute kidney injury predictive models using non‐standard EMRs in resource‐limited settings
Non-standard EMRs are valuable for predicting AKI, even in the absence of SCr data. This approach is particularly useful in resource-limited settings, where traditional biomarkers are often unavailable, demonstrating the potential of other clinical features to compensate for missing SCr data in AKI prediction.
Authors
- Lang Zhou
- Qi Cheng (ORCID: https://orcid.org/0000-0003-4336-3082)
- Yuanhan Chen
- Yuanjiang Liao (ORCID: https://orcid.org/0000-0002-3193-5867)
- Rui Fang (ORCID: https://orcid.org/0000-0001-6075-9201)
- Xinling Liang (ORCID: https://orcid.org/0000-0002-6764-9571)
- Jing Sun (ORCID: https://orcid.org/0000-0002-2454-5553)
- Zhen Xie (ORCID: https://orcid.org/0000-0003-0722-5168)
- Yanhua Wu (ORCID: https://orcid.org/0000-0002-2803-809X)
- Yu Kuang (ORCID: https://orcid.org/0000-0001-9451-4640)
- Hao Li (ORCID: https://orcid.org/0000-0002-4131-5207)
- Qin Zhang (ORCID: https://orcid.org/0000-0002-4597-7697)
- Lu Chen (ORCID: https://orcid.org/0000-0002-7216-7673)
- Guohui Liu (ORCID: https://orcid.org/0000-0002-2013-1396)
- Feng Ding (ORCID: https://orcid.org/0000-0001-7856-1834)
- Shengwen Guo
- Qiushi Luo (ORCID: https://orcid.org/0000-0001-8440-4800)
- Ziqiang Chen (ORCID: https://orcid.org/0000-0001-7779-1478)
- Haiquan Huang
- Qiang He (ORCID: https://orcid.org/0000-0003-1640-1776)
Institutions
- Zhejiang Chinese Medical University (CN)
- University of Nevada, Las Vegas (US)
- University of Electronic Science and Technology of China (CN)
- North China Electric Power University (CN)
- Anhui Medical University (CN)
- China Guangzhou Analysis and Testing Center (CN)
- Shanghai Ninth People's Hospital (CN)
- University Medical Center of Southern Nevada (US)
- People's Hospital of Xinjiang Uygur Autonomous Region (CN)
- Dongguan People’s Hospital (CN)
- Tibet Autonomous Region People's Hospital (CN)
- Second Affiliated Hospital of Jilin University (CN)
- Guangdong Institute of Intelligent Manufacturing (CN)
- Guangdong Academy of Medical Sciences (CN)
- Second Affiliated Hospital of Anhui Medical University (CN)
- First People's Hospital of Chongqing (CN)
- Southern Medical University (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-09-29
- DOI
- https://doi.org/10.1002/mp.70038
- Citations
- 2
- Primary Topic
- Acute Kidney Injury Research
- Type
- article
- Field-Weighted Citation Impact
- 2.86
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Tibet Autonomous Region