Discriminative Machine Learning Analysis for Skin Microbiome: Observing Biomarkers in Patients with Seborrheic Dermatitis-Reference-Cited by-同舟云学术

Discriminative Machine Learning Analysis for Skin Microbiome: Observing Biomarkers in Patients with Seborrheic Dermatitis

Published:2022 Issue:0-0 Volume:0 Page:1-7
ISSN:2666-1470
Container-title:Journal of Artificial Intelligence for Medical Sciences
language:
Short-container-title:JoAIMS

Author:

van der Wall H.E.C.,Doll R.J.,van Westen G.J.P.,Niemeyer-van der Kolk T.,Feiss G.,Pinckaers H.,van Doorn M.B.A.,Nijsten T.,Sanders M.G.H.,Cohen A.F.,Burggraaf J.,Rissmann R.,Pardo L.M.

Abstract

Publisher

KEO Tongda (Henan) Information Technology Co., Ltd

Subject

General Medicine

Reference36 articles.

1. 1.E.A. Grice, J.A. Segre, The skin microbiome, Nat. Rev. Microbiol. 9 (2011), 244-253. https://doi.org/10.1038/nrmicro2537

2. 2.M. Garcia-Garcerà, K. Garcia-Etxebarria, M. Coscollà, A. Latorre, F. Calafell, A new method for extracting skin microbes allows metagenomic analysis of whole-deep skin, PLoS ONE. 8 (2013), e74914. https://doi.org/10.1371/journal.pone.0074914

3. 3.P.L.J.M. Zeeuwen, M. Kleerebezem, H.M. Timmerman, J. Schalkwijk, Microbiome and skin diseases, Curr. Opin. Allergy Clin. Immunol. 13 (2013), 514-520. https://doi.org/10.1097/aci.0b013e328364ebeb

4. 4.M. Leclercq, B. Vittrant, M.L. Martin-Magniette, M.P. Scott Boyer, O. Perin, A. Bergeron, et al., Large-scale automatic feature selection for biomarker discovery in high-dimensional OMICs data, Front. Genet. 10 (2019), 452. https://doi.org/10.3389/fgene.2019.00452

5. 5.D. Zhang, D. Shen, The Alzheimer's Disease Neuroimaging Initiative, Multi-modal multi-task learning for joint prediction of multiple regression and classification variables in Alzheimer's disease, NeuroImage. 59 (2012), 895-907. https://doi.org/10.1016/j.neuroimage.2011.09.069