Comparative Analysis of Salivary pH Alterations Following Sugar Consumption Using Machine Learning Techniques

DOI

10.2991/978-94-6239-654-8_15How to use a DOI?

Keywords

Dental caries; Fermentation; Sucrose; Saliva; Buffer

Abstract

The pH of saliva is a very important indicator of oral health because continued acidic environments favor caries in the mouth. Commercial sugars available in the market have different acidogenic capabilities associated with them, and they lead to a different acidogenic effect on salivary pH after consumption. This paper offers a machine learning method of relatively comparing the change in salivary pH in presence of sugars commonly ingested. The samples of saliva were taken on an empty stomach of healthy subjects at the baseline level and at certain times following the consumption of white sugar, brown sugar, jaggery, honey, and artificial sweeteners. The data was comprised of demographics, type of sugar, and amount of sugars, time, and reference pH before consumption, and post-consumption pH. The preprocessing was followed by a Random Forest model that was used to predict the changes in pH and to classify sugars according to their acidogenic potential. The presented model was characterized by a high predictive quality; the type of sugar and the duration of consumption were accepted as the most significant factors that impact pH decrease. Refined sugars experienced a higher loss of pH than natural and artificial versions. The given method emphasises the perspectives of machine learning in dental studies in terms of objective evaluation and preventive oral health planning.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Amutha M. V. Soorya
AU  - Vishnu Rekha Chamarthi
AU  - Santhosh Priya
AU  - Dhanraj Kalaivanan
AU  - Santham Krishnamoorthy
PY  - 2026
DA  - 2026/04/24
TI  - Comparative Analysis of Salivary pH Alterations Following Sugar Consumption Using Machine Learning Techniques
BT  - Proceedings of the Global Conference on Sustainable Energy Systems, Smart Electronics and Intelligent Computing (GCSESEIC 2025)
PB  - Atlantis Press
SP  - 160
EP  - 171
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6239-654-8_15
DO  - 10.2991/978-94-6239-654-8_15
ID  - Soorya2026
ER  -