Predicting blood glucose level using salivary glucose and other associated factors: A machine learning model selection and evaluation study

Introduction: There is a need for designing non-invasive methods to predict blood glucose levels to ensure timely diagnosis of Diabetes Mellitus. Needle anxiety and bleeding disorders preclude many from undertaking blood tests. Objectives: The primary objective of this study was to assess if biomark...

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Bibliographic Details

Published in:	Informatics in Medicine Unlocked
Main Authors:	Aditi Chopra, Rohini R. Rao, Shobha U. Kamath, Sanjana Akhila Arun, Laasya Shettigar
Format:	Article
Language:	English
Published:	Elsevier 2024-01-01
Subjects:	Blood glucose level Confirmatory prediction Diabetes mellitus Feature selection Machine learning model Non-invasive method
Online Access:	http://www.sciencedirect.com/science/article/pii/S2352914824000790