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Cited by in F6Publishing
For: Wu H, Cai L, Li D, Wang X, Zhao S, Zou F, Zhou K. Metagenomics Biomarkers Selected for Prediction of Three Different Diseases in Chinese Population. Biomed Res Int 2018;2018:2936257. [PMID: 29568746 DOI: 10.1155/2018/2936257] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 1.5] [Reference Citation Analysis]
Number Citing Articles
1 Stafford IS, Kellermann M, Mossotto E, Beattie RM, MacArthur BD, Ennis S. A systematic review of the applications of artificial intelligence and machine learning in autoimmune diseases. NPJ Digit Med. 2020;3:30. [PMID: 32195365 DOI: 10.1038/s41746-020-0229-3] [Cited by in Crossref: 20] [Cited by in F6Publishing: 11] [Article Influence: 10.0] [Reference Citation Analysis]
2 Bang S, Yoo D, Kim SJ, Jhang S, Cho S, Kim H. Establishment and evaluation of prediction model for multiple disease classification based on gut microbial data. Sci Rep 2019;9:10189. [PMID: 31308384 DOI: 10.1038/s41598-019-46249-x] [Cited by in Crossref: 9] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
3 Zhou YH, Gallins P. A Review and Tutorial of Machine Learning Methods for Microbiome Host Trait Prediction.Front Genet. 2019;10:579. [PMID: 31293616 DOI: 10.3389/fgene.2019.00579] [Cited by in Crossref: 50] [Cited by in F6Publishing: 41] [Article Influence: 16.7] [Reference Citation Analysis]
4 Kumar P, Sinha R, Shukla P. Artificial intelligence and synthetic biology approaches for human gut microbiome. Crit Rev Food Sci Nutr 2020;:1-19. [PMID: 33249867 DOI: 10.1080/10408398.2020.1850415] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
5 Iadanza E, Fabbri R, Bašić-čičak D, Amedei A, Telalovic JH. Gut microbiota and artificial intelligence approaches: A scoping review. Health Technol 2020;10:1343-58. [DOI: 10.1007/s12553-020-00486-7] [Cited by in Crossref: 5] [Cited by in F6Publishing: 1] [Article Influence: 2.5] [Reference Citation Analysis]
6 Curry KD, Nute MG, Treangen TJ. It takes guts to learn: machine learning techniques for disease detection from the gut microbiome. Emerg Top Life Sci 2021;5:815-27. [PMID: 34779841 DOI: 10.1042/ETLS20210213] [Reference Citation Analysis]
7 Xiang L, Jin X, Liu Y, Ma Y, Jian Z, Wei Z, Li H, Li Y, Wang K. Prediction of the occurrence of calcium oxalate kidney stones based on clinical and gut microbiota characteristics. World J Urol 2021. [PMID: 34427737 DOI: 10.1007/s00345-021-03801-7] [Reference Citation Analysis]
8 Marcos-Zambrano LJ, Karaduzovic-Hadziabdic K, Loncar Turukalo T, Przymus P, Trajkovik V, Aasmets O, Berland M, Gruca A, Hasic J, Hron K, Klammsteiner T, Kolev M, Lahti L, Lopes MB, Moreno V, Naskinova I, Org E, Paciência I, Papoutsoglou G, Shigdel R, Stres B, Vilne B, Yousef M, Zdravevski E, Tsamardinos I, Carrillo de Santa Pau E, Claesson MJ, Moreno-Indias I, Truu J. Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment. Front Microbiol 2021;12:634511. [PMID: 33737920 DOI: 10.3389/fmicb.2021.634511] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 10.0] [Reference Citation Analysis]