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Cited by in CrossRef
For: Cai SS, Zheng TY, Wang KY, Zhu HP. Clinical study of different prediction models in predicting diabetic nephropathy in patients with type 2 diabetes mellitus. World J Diabetes 2024; 15(1): 43-52 [PMID: 38313855 DOI: 10.4239/wjd.v15.i1.43]
URL: https://www.wjgnet.com/1948-9358/full/v15/i1/43.htm
Number Citing Articles
1
Alyaa Hliel, Huda Ahmed, Hiba Hasan. Assessment and prediction of diabetic kidney disease in patients with type 2 diabetes mellitus by using an advanced biomarkersNefrología 2025;  doi: 10.1016/j.nefro.2025.03.001
2
Fayez Althobaiti, Ehab S. Taher, Lamya Ahmed Alkeridis, Ateya M. Ibrahim, Nagi El-Shafai, Laila A Al-Shuraym, Liana Fericean, Florin Imbrea, Mohamed A Kassab, Foad A. Farrag, Ahmed Abdeen, Daklallah A. Almalki, Ammar AL-Farga, Mohamed Afifi, Mustafa Shukry. Exploring the NRF2/HO-1 and NF-κB Pathways: Spirulina Nanoparticles as a Novel Approach to Combat Diabetic NephropathyACS Omega 2024; 9(22): 23949 doi: 10.1021/acsomega.4c02285
3
Changmao Dai, Xiaolan Sun, Jia Xu, Maojun Chen, Wei Chen, Xueping Li. The accuracy of Machine learning in the prediction and diagnosis of diabetic kidney Disease: A systematic review and Meta-AnalysisInternational Journal of Medical Informatics 2025; : 105975 doi: 10.1016/j.ijmedinf.2025.105975
4
Yihan Li, Nan Jin, Qiuzhong Zhan, Yue Huang, Aochuan Sun, Fen Yin, Zhuangzhuang Li, Jiayu Hu, Zhengtang Liu. Machine learning-based risk predictive models for diabetic kidney disease in type 2 diabetes mellitus patients: a systematic review and meta-analysisFrontiers in Endocrinology 2025; 16 doi: 10.3389/fendo.2025.1495306
5
Shiny Manuel, Chinnathambipalayam Kandasamy Vijayasamundeeswari, Kamala Kanta Parhi, Sudha Rangasamy. Evaluation of Serum Beta-trace Protein for Identifying Nephropathy in Type 2 Diabetes MellitusBiomedical and Biotechnology Research Journal 2025; 9(1): 100 doi: 10.4103/bbrj.bbrj_46_25