Machine Learning Approach Identified Multi-Platform Factors for Caries Prediction in Child-Mother Dyads.

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Bibliographic Details
Title: Machine Learning Approach Identified Multi-Platform Factors for Caries Prediction in Child-Mother Dyads.
Authors: Wu TT; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, United States., Xiao J; Eastman Institute for Oral Health, University of Rochester Medical Center, Rochester, NY, United States., Sohn MB; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, United States., Fiscella KA; Department of Family Medicine, University of Rochester Medical Center, Rochester, NY, United States., Gilbert C; Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY, United States., Grier A; Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY, United States., Gill AL; Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY, United States., Gill SR; Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY, United States.
Source: Frontiers in cellular and infection microbiology [Front Cell Infect Microbiol] 2021 Aug 19; Vol. 11, pp. 727630. Date of Electronic Publication: 2021 Aug 19 (Print Publication: 2021).
Publication Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.
Journal Info: Publisher: Frontiers Media SA Country of Publication: Switzerland NLM ID: 101585359 Publication Model: eCollection Cited Medium: Internet ISSN: 2235-2988 (Electronic) Linking ISSN: 22352988 NLM ISO Abbreviation: Front Cell Infect Microbiol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2235-2988
DOI:10.3389/fcimb.2021.727630