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• W4283329415 abstract "Although various skin cancer detection devices have been proposed, most of them are not used owing to their insufficient diagnostic accuracies. Laser-induced plasma spectroscopy (LIPS) can noninvasively extract biochemical information of skin lesions using an ultrashort pulsed laser.To investigate the diagnostic accuracy and safety of real-time noninvasive in vivo skin cancer diagnostics utilizing nondiscrete molecular LIPS combined with a deep neural network (DNN)-based diagnostic algorithm.In vivo LIPS spectra were acquired from 296 skin cancers (186 basal cell carcinomas, 96 squamous cell carcinomas, and 14 melanomas) and 316 benign lesions in a multisite clinical study. The diagnostic performance was validated using 10-fold cross-validations.The sensitivity and specificity for differentiating skin cancers from benign lesions using LIPS and the DNN-based algorithm were 94.6% (95% CI: 92.0%-97.2%) and 88.9% (95% CI: 85.5%-92.4%), respectively. No adverse events, including macroscopic or microscopic visible marks or pigmentation due to laser irradiation, were observed.The diagnostic performance was evaluated using a limited data set. More extensive clinical studies are needed to validate these results.This LIPS system with a DNN-based diagnostic algorithm is a promising tool to distinguish skin cancers from benign lesions with high diagnostic accuracy in real clinical settings." @default.
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• W4283329415 date "2023-07-01" @default.
• W4283329415 modified "2023-09-26" @default.
• W4283329415 title "Real-time, in vivo skin cancer triage by laser-induced plasma spectroscopy combined with a deep learning–based diagnostic algorithm" @default.
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• W4283329415 doi "https://doi.org/10.1016/j.jaad.2022.06.1166" @default.
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