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Cited by in F6Publishing

For:	Liu J, Li J, Li W, Li N, Huo X, Wang H, Leng J, Yu Z, Ma RCW, Hu G, Fang Z, Yang X. Predictive values of serum metabolites in early pregnancy and their possible pathways for gestational diabetes: A nested case-control study in Tianjin, China. J Diabetes Complications 2021;35:108048. [PMID: 34563440 DOI: 10.1016/j.jdiacomp.2021.108048] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]

For:

Liu J, Li J, Li W, Li N, Huo X, Wang H, Leng J, Yu Z, Ma RCW, Hu G, Fang Z, Yang X. Predictive values of serum metabolites in early pregnancy and their possible pathways for gestational diabetes: A nested case-control study in Tianjin, China. J Diabetes Complications 2021;35:108048. [PMID: 34563440 DOI: 10.1016/j.jdiacomp.2021.108048] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]

Number	Citing Articles
1	Wang Y, Pan XF, Pan A. Lipidomics in gestational diabetes mellitus. Curr Opin Lipidol 2023;34:1-11. [PMID: 36637074 DOI: 10.1097/MOL.0000000000000858] [Reference Citation Analysis]
2	Xie J, Li L, Xing H. Metabolomics in gestational diabetes mellitus: A review. Clin Chim Acta 2023;539:134-43. [PMID: 36529269 DOI: 10.1016/j.cca.2022.12.005] [Reference Citation Analysis]
3	Mennickent D, Rodríguez A, Farías-jofré M, Araya J, Guzmán-gutiérrez E. Machine learning-based models for gestational diabetes mellitus prediction before 24–28 weeks of pregnancy: A review. Artificial Intelligence in Medicine 2022. [DOI: 10.1016/j.artmed.2022.102378] [Reference Citation Analysis]