Application of Surface-Enhanced Raman Spectroscopy and Machine Learning Omics Techniques in the Progression Assessment of Autosomal Dominant Polycystic Kidney Disease
Urinary SERS detection can distinguish RP ADPKD patients from SP ones noninvasively, conveniently and quickly, with reasonable accuracy, sensitivity, and specificity. SERS combined with machine learning omics techniques might be a novel method to evaluate the progression of ADPKD.
Authors
- Huinan Yang (ORCID: https://orcid.org/0000-0002-4839-7911)
- Cheng Xue (ORCID: https://orcid.org/0000-0002-4132-9406)
- Jing Xu (ORCID: https://orcid.org/0000-0001-9946-4769)
- Rui Cheng (ORCID: https://orcid.org/0000-0002-0776-1692)
- Zhiguo Mao (ORCID: https://orcid.org/0000-0002-6591-4538)
- Fangzheng Cui (ORCID: https://orcid.org/0009-0005-7723-7764)
Institutions
- University of Shanghai for Science and Technology (CN)
- 307th Hospital of Chinese People’s Liberation Army (CN)
- Shanghai Changzheng Hospital (CN)
- 181st Hospital of Chinese People's Liberation Army (CN)
- Chinese People’s Liberation Army 263 hospital (CN)
Publication Details
- Journal
- Kidney Diseases
- Published
- 2025-09-29
- DOI
- https://doi.org/10.1159/000548579
- Citations
- 1
- Primary Topic
- Genetic and Kidney Cyst Diseases
- Type
- article
- Field-Weighted Citation Impact
- 1.82
Funders
- National Natural Science Foundation of China
- Science and Technology Commission of Shanghai Municipality
- Science and Technology Innovation Plan Of Shanghai Science and Technology Commission