Integration of the fluorescence based portable device with the AI tools for the real-time monitoring of oral mucosal lesions

There is a need for non-invasive, sensitive, real-time, and user-friendly optical devices integrated with artificial intelligence (AI) based tools for the detection of oral mucosal lesions at early stage. Research on the development of optical devices has been executed by several research groups for the cancer detection and it is still being continued. We have also contributed towards it by developing a steady- state fluorescence-based portable device. The in-house developed device is equipped with 405 nm laser diode, UV visible spectrometer, optical components, and other accessories. Laser light irradiated on the oral cavity of diseased (cancerous) and non-diseased (normal) groups, excites the two endogenous fluorophores namely FAD and porphyrin. We observed an enhancement in the porphyrin fluorescence of cancerous patients (OSCC and Dysplasia) than the normal group. Data analysis carried out by AI tools i.e., Naïve Bayes, LDA, and QDA showed slightly higher accuracy for QDA. QDA was able to discriminate among Normal to OSCC, Normal to Dysplasia, and Dysplasia to OSCC with accuracies of 95.34%, 100%, and 97.43% respectively.

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Publication Details

Journal
Scientific Reports
Published
2025-03-25
DOI
https://doi.org/10.1038/s41598-025-94676-w
Citations
6
Primary Topic
Oral Health Pathology and Treatment
Type
article
Field-Weighted Citation Impact
8.79
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article

Integration of the fluorescence based portable device with the AI tools for the real-time monitoring of oral mucosal lesions

Pavan Kumar, Shashikant Rathod
6 citations
Scientific Reports
Oral Health Pathology and Treatment
8.79
article

Integration of the fluorescence based portable device with the AI tools for the real-time monitoring of oral mucosal lesions

Pavan Kumar, Shashikant Rathod
article en
6 citations

Abstract

There is a need for non-invasive, sensitive, real-time, and user-friendly optical devices integrated with artificial intelligence (AI) based tools for the detection of oral mucosal lesions at early stage. Research on the development of optical devices has been executed by several research groups for the cancer detection and it is still being continued. We have also contributed towards it by developing a steady- state fluorescence-based portable device. The in-house developed device is equipped with 405 nm laser diode, UV visible spectrometer, optical components, and other accessories. Laser light irradiated on the oral cavity of diseased (cancerous) and non-diseased (normal) groups, excites the two endogenous fluorophores namely FAD and porphyrin. We observed an enhancement in the porphyrin fluorescence of cancerous patients (OSCC and Dysplasia) than the normal group. Data analysis carried out by AI tools i.e., Naïve Bayes, LDA, and QDA showed slightly higher accuracy for QDA. QDA was able to discriminate among Normal to OSCC, Normal to Dysplasia, and Dysplasia to OSCC with accuracies of 95.34%, 100%, and 97.43% respectively.

Scientific ReportsVol. 15(1)
General Motors (India) (IN), Datta Meghe Institute of Higher Education and Research (IN), Indian Institute of Technology Kanpur (IN)
Reduced inequalities
Openalex Percentile: Top 2%
Oral Health Pathology and Treatment
8.79
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