WEI LIANG1,2,*, ZONGWEI ZHANG1,2, KEJU YANG1,2,3, HONGTU HU1,2, QIANG LUO1,2, ANKANG YANG1,2, LI CHANG4, YUANYUAN ZENG4
BIOCELL, Vol.47, No.6, pp. 1253-1263, 2023, DOI:10.32604/biocell.2023.027373
Abstract Background: Diabetic nephropathy (DN) is the most common complication of type 2 diabetes mellitus and the
main cause of end-stage renal disease worldwide. Diagnostic biomarkers may allow early diagnosis and treatment of DN
to reduce the prevalence and delay the development of DN. Kidney biopsy is the gold standard for diagnosing DN;
however, its invasive character is its primary limitation. The machine learning approach provides a non-invasive and
specific criterion for diagnosing DN, although traditional machine learning algorithms need to be improved to
enhance diagnostic performance. Methods: We applied high-throughput RNA sequencing to obtain the genes related
to DN tubular… More >
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