Prediction of ultrafiltration volume in maintenance hemodialysis patients using an artificial neural network model based on body composition information
This study effectively demonstrates the predictive role of an artificial neural network model based on pre-dialysis body composition information in estimating ultrafiltration providing a valuable predictive tool to optimize assessment volume for MHD patients, of ultrafiltration volume in MHD patients.
Authors
- Lirong He (ORCID: https://orcid.org/0000-0002-8106-756X)
- Jurong Yang (ORCID: https://orcid.org/0000-0002-6792-4617)
- Xinghua Lu (ORCID: https://orcid.org/0000-0003-3137-8586)
- Jinrong Peng (ORCID: https://orcid.org/0000-0001-9911-8444)
- Jiaoyan Chen (ORCID: https://orcid.org/0000-0003-4643-6750)
- Yunyan Wang (ORCID: https://orcid.org/0000-0002-0866-4640)
- Wei Tan
- Qing Yu (ORCID: https://orcid.org/0009-0007-8587-6974)
Institutions
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-11-11
- DOI
- https://doi.org/10.1186/s12911-025-03248-5
- Primary Topic
- Dialysis and Renal Disease Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00