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Cited by in F6Publishing
For: Zhu YX, Huang JQ, Ming YY, Zhuang Z, Xia H. Screening of key biomarkers of tendinopathy based on bioinformatics and machine learning algorithms. PLoS One 2021;16:e0259475. [PMID: 34714891 DOI: 10.1371/journal.pone.0259475] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Ren K, Wang L, Wang Y, An G, Du Q, Cao J, Jin Q, Yun K, Guo Z, Wang Y, Liang Q, Sun J. Wound age estimation based on next-generation sequencing: Fitting the optimal index system using machine learning. Forensic Science International: Genetics 2022. [DOI: 10.1016/j.fsigen.2022.102722] [Reference Citation Analysis]
2 Han X, Song D. Using a Machine Learning Approach to Identify Key Biomarkers for Renal Clear Cell Carcinoma. IJGM 2022;Volume 15:3541-58. [DOI: 10.2147/ijgm.s351168] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Zhang J, Huang C, Liu Z, Ren S, Shen Z, Han K, Xin W, He G, Liu J, Wang F. Screening of Potential Biomarkers in the Peripheral Serum for Steroid-Induced Osteonecrosis of the Femoral Head Based on WGCNA and Machine Learning Algorithms. Disease Markers 2022;2022:1-17. [DOI: 10.1155/2022/2639470] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]