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Cited by in F6Publishing

For:	Alber S, Kumar S, Liu J, Huang Z, Paez D, Hong J, Chang H, Bhutani T, Gensler LS, Liao W. Single Cell Transcriptome and Surface Epitope Analysis of Ankylosing Spondylitis Facilitates Disease Classification by Machine Learning. Front Immunol 2022;13:838636. [DOI: 10.3389/fimmu.2022.838636] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]

For:

Alber S, Kumar S, Liu J, Huang Z, Paez D, Hong J, Chang H, Bhutani T, Gensler LS, Liao W. Single Cell Transcriptome and Surface Epitope Analysis of Ankylosing Spondylitis Facilitates Disease Classification by Machine Learning. Front Immunol 2022;13:838636. [DOI: 10.3389/fimmu.2022.838636] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]

Number	Citing Articles
1	Ning D, Garg K, Mayer B, Schick B, Bracht H, Barth E, Weiss M, Li C, Schneider J, Schneider EM. Monocyte subtype expression patterns in septic patients with diabetes are distinct from patterns observed in obese patients. Front Med (Lausanne) 2022;9:1026298. [PMID: 36687421 DOI: 10.3389/fmed.2022.1026298] [Reference Citation Analysis]
2	Zhu J, Lu Q, Liang T, JieJiang, Li H, Zhou C, Wu S, Chen T, Chen J, Deng G, Yao Y, Liao S, Yu C, Huang S, Sun X, Chen L, Chen W, Ye Z, Guo H, Chen W, Jiang W, Fan B, Tao X, Zhan X, Liu C. Development and Validation of a Machine Learning-Based Nomogram for Prediction of Ankylosing Spondylitis. Rheumatol Ther 2022. [PMID: 35932360 DOI: 10.1007/s40744-022-00481-6] [Cited by in F6Publishing: 1] [Reference Citation Analysis]