Unexpected Clinical and Dermoscopic Advancement of Nevoid Basal Cell Carcinoma Syndrome Despite Cemiplimab Therapy

Results:The area under the curve (AUC) metric was used to quantify the model's ability to discriminate between targets based on their Raman spectra.The AUC results are detailed in Figure 1 highlighting the high discriminative performance Figure 1: The AUC results for different target comparisons highlighting the high discriminative performance across most categories.The AI model demonstrated high precision in characterizing microscopic structures targeted by LC-OCT, leveraging the specificity of CRM.The AUC results from the developed model confirm its ability to accurately distinguish between various regions within BCC.Conclusions: This is the first study combining 3D microscopic imaging-guided Raman spectroscopy with AI for target characterization.It accurately characterizes BCC tumor structures, enhancing diagnostic precision and advancing understanding of the tumor microenvironment, with potential to improve dermatological diagnostics and therapies