Proceedings of the 2nd International Conference on Recent Advancement and Modernization in Sustainable Intelligent Technologies & Applications (RAMSITA-2026)

<Previous Article In Volume
Next Article In Volume>

A Computational Approach for Identification of Salivary Biomarkers

Authors
Krunal Parate1, *, Arpita Parakh1
1Department of Biomedical Engineering, Shri Ramdeobaba College of Engineering and Management, Nagpur, India
*Corresponding author. Email: paratekc@rknec.edu
Corresponding Author
Krunal Parate
Available Online 28 May 2026.
DOI
10.2991/978-94-6239-678-4_2How to use a DOI?
Keywords
Saliva; Biomarkers; Non-invasive diagnosis; Salivary diagnostics; Oral health; Disease detection; Point-of-care testing
Abstract

Atransparent, readily accessible bodily fluid, salivais essential for maintaining oral health. Numerous biological substances that are useful for illness detection are also present. Saliva has drawn interest recently as a non-invasive, reasonably priced method of diagnosing a range of illnesses. The kinds of chemicals found in saliva that can function as biomarkers are described in this overview, including proteins, Deoxyribonucleic acid (DNA), Ribonucleic acid(RNA), and metabolites. Diabetes, heart disease, and oral cancer can all be detected and tracked with the use of these biomarkers. Saliva collection is easy, safe, and painless, which makes it perfect for routinemedical examinations. The difficulties in using saliva for diagnosis are also covered in this research, including sample storage and guaranteeing reliable results. In spite of these obstacles, continuous. Saliva-based testing is getting better because to continued research, despite these obstacles. Saliva biomarkers have the potential to be a standard component of medical diagnostics in the future, particularly for early illness identification.

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.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2nd International Conference on Recent Advancement and Modernization in Sustainable Intelligent Technologies & Applications (RAMSITA-2026)
Series
Advances in Intelligent Systems Research
Publication Date
28 May 2026
ISBN
978-94-6239-678-4
ISSN
1951-6851
DOI
10.2991/978-94-6239-678-4_2How to use a DOI?
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.

Cite this article

risenwbib
TY  - CONF
AU  - Krunal Parate
AU  - Arpita Parakh
PY  - 2026
DA  - 2026/05/28
TI  - A Computational Approach for Identification of Salivary Biomarkers
BT  - Proceedings of the 2nd International Conference on Recent Advancement and Modernization in Sustainable Intelligent Technologies & Applications (RAMSITA-2026)
PB  - Atlantis Press
SP  - 7
EP  - 19
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-678-4_2
DO  - 10.2991/978-94-6239-678-4_2
ID  - Parate2026
ER  -