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

被引:2
作者
Kumar, Pavan [1 ,2 ]
Rathod, Shashikant [3 ,4 ]
机构
[1] Datta Meghe Inst Higher Educ & Res DMIHER, Fac Engn & Technol FEAT, Wardha 442001, India
[2] Indian Inst Technol Kanpur IITK, Dept Phys, Kanpur 208016, India
[3] COEP Technol Univ, Dept Instrumentat & Control Engn, Pune 411005, India
[4] Program Launch Management Analyt, FORDS Motors Pvt Ltd, Chennai 600119, India
关键词
Oral mucosal lesions; Fluorescence spectroscopy; Porphyrin; AI tools; AUTOFLUORESCENCE SPECTROSCOPY; CANCER; DIAGNOSIS; CLASSIFICATION; SPECTRA;
D O I
10.1038/s41598-025-94676-w
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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., Na & iuml;ve 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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页数:9
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