Non-destructive classification of type 2 diabetic teeth using LIBS-derived elemental biomarkers and machine learning.
- DOI
- 10.1016/j.aca.2026.345615
- Published
- 2026 Aug 8
- Container
- Analytica chimica acta
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.aca.2026.345615,
title = {Non-destructive classification of type 2 diabetic teeth using LIBS-derived elemental biomarkers and machine learning.},
author = {Dastageer MM and Siraj K and Senesi GS and Israr MA and Haq SU},
year = {2026},
journal = {Analytica chimica acta},
doi = {10.1016/j.aca.2026.345615},
url = {https://doi.org/10.1016/j.aca.2026.345615}
}RIS
TY - JOUR TI - Non-destructive classification of type 2 diabetic teeth using LIBS-derived elemental biomarkers and machine learning. AU - Dastageer MM AU - Siraj K AU - Senesi GS AU - Israr MA AU - Haq SU PY - 2026 JO - Analytica chimica acta DO - 10.1016/j.aca.2026.345615 UR - https://doi.org/10.1016/j.aca.2026.345615 ER -
APA
MM, D., K, S., GS, S., MA, I., & SU, H. (2026). Non-destructive classification of type 2 diabetic teeth using LIBS-derived elemental biomarkers and machine learning.. Analytica chimica acta. https://doi.org/10.1016/j.aca.2026.345615
Source records
- pubmed · retrieved 2026-09-24T23:45:49.488Z