Artificial intelligence–based diagnosis of diabetic kidney disease using urinary VOC biosensor data
Urinary VOC-based machine learning models provide proof-of-concept evidence for non-invasive DKD diagnosis. Random Forest, in particular, shows potential as a triage tool to differentiate DKD from other glomerular conditions, which may in the future help reduce reliance on biopsy and support earlier identification in nephrology practice.
Authors
- Chatchai Kreepala (ORCID: https://orcid.org/0000-0002-2615-4222)
- Watcharapong Anakkamatee (ORCID: https://orcid.org/0009-0003-4803-5245)
- Anawin Pechbooranin
Institutions
- Naresuan University (TH)
- Suranaree University of Technology (TH)
Publication Details
- Journal
- BMC Nephrology
- Published
- 2025-11-26
- DOI
- https://doi.org/10.1186/s12882-025-04608-z
- Primary Topic
- Advanced Chemical Sensor Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Suranaree University of Technology