Development of a machine learning multiclass screening tool for periodontal health status based on non-clinical parameters and salivary biomarkers.

Ke Deng; Francesco Zonta; Huang Yang; George Pelekos; Maurizio Tonetti

Development of a machine learning multiclass screening tool for periodontal health status based on non-clinical parameters and salivary biomarkers.

Ke Deng, Francesco Zonta, Huang Yang, George Pelekos, Maurizio Tonetti

Department of Biosciences and Bioinformatics

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

Original language	English
Journal	Journal of Clinical Periodontology
Publication status	Published - Sept 2023

Cite this

@article{948577a94d414bb9b3a0705d0e22a01f,

title = "Development of a machine learning multiclass screening tool for periodontal health status based on non-clinical parameters and salivary biomarkers.",

author = "Ke Deng and Francesco Zonta and Huang Yang and George Pelekos and Maurizio Tonetti",

year = "2023",

month = sep,

language = "English",

journal = "Journal of Clinical Periodontology",

issn = "0303-6979",

}

TY - JOUR

T1 - Development of a machine learning multiclass screening tool for periodontal health status based on non-clinical parameters and salivary biomarkers.

AU - Deng, Ke

AU - Zonta, Francesco

AU - Yang, Huang

AU - Pelekos, George

AU - Tonetti, Maurizio

PY - 2023/9

Y1 - 2023/9

M3 - Article

C2 - 37697491

SN - 0303-6979

JO - Journal of Clinical Periodontology

JF - Journal of Clinical Periodontology

ER -