Publication:
Enhancing Periodontal Treatment Through the Integration of Deep Learning-Based Detection with Bayesian Network Models

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Issued Date

2024-08-22

Resource Type

Conference Paper

ISSN

09269630

eISSN

18798365

DOI

10.3233/SHTI240758

Scopus ID

2-s2.0-85201997977

Pubmed ID

39176544

Journal Title

Studies in Health Technology and Informatics

Volume

316

Start Page

1729

End Page

1730

Rights Holder(s)

SCOPUS

Bibliographic Citation

Studies in Health Technology and Informatics Vol.316 (2024) , 1729-1730

Suggested Citation

Thanathornwong B., Ouivirach K., Wuttisarnwattana P., Wongsapai M., Suebnukarn S. Enhancing Periodontal Treatment Through the Integration of Deep Learning-Based Detection with Bayesian Network Models. Studies in Health Technology and Informatics Vol.316 (2024) , 1729-1730. 1730. doi:10.3233/SHTI240758 Retrieved from: https://hdl.handle.net/20.500.14740/20908

Title

Enhancing Periodontal Treatment Through the Integration of Deep Learning-Based Detection with Bayesian Network Models

Author(s)

Thanathornwong B.
 Ouivirach K.
 Wuttisarnwattana P.
 Wongsapai M.
 Suebnukarn S.

Author's Affiliation

Thammasat University
 Chiang Mai University
 Srinakharinwirot University
 ODDS
 Intercountry Centre for Oral Health

Corresponding Author(s)

Thanathornwong B.

Other Contributor(s)

Srinakharinwirot University

Abstract

This study incorporated deep learning for periodontal disease detection into a Bayesian network (BN) clinical decision support model for comprehensive periodontal care. BN structure and probabilities were based on clinical data and Faster R-CNN-detected radiographic images. Receiver operating characteristic curve analysis confirmed the model's high accuracy in treatment plan recommendations.

Keyword(s)

Engineering
 Medicine
 Health Professions

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URI

https://hdl.handle.net/20.500.14740/20908

Collections

Scopus: Year 2024

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