Abstract / Summary
Dermoscopy improves the diagnosis of melanoma and keratinocyte carcinoma, but its value depends on the observer, the lesion mix, the anatomic site, and the action taken after the examination. Recent reviews have mainly focused on one modality or image-classification accuracy. This narrative review follows the clinical pathway and compares five linked areas: defined diagnostic criteria, sequential digital monitoring, site- and skin-tone-specific interpretation, multimodal imaging, and artificial intelligence (AI). Melanoma and keratinocyte carcinoma are discussed separately because their criteria, diagnostic problems, imaging needs, and management differ. Meta-analyses support dermoscopy over naked-eye examination, although accuracy remains closely related to clinician experience. A randomized trial of three-dimensional total-body photography with sequential dermoscopy led to more procedures and higher costs without finding more malignant tumors over two years. Reflectance confocal microscopy can improve specificity in selected equivocal lesions, while optical coherence technologies add architectural and depth information that is most relevant to keratinocyte carcinoma. AI has moved from retrospective benchmarks to prospective multicenter studies, but false-positive burden, dataset shift, underrepresentation of darker skin tones, limited explainability, and uncertain workflow effects remain. The review also considers foundation models, regulation, and patient-facing tools and uses a SWOT analysis to define research priorities. The field is at an inflection point in evidence, not image quality. Progress should be judged by effects on biopsy decisions, missed-cancer rates, timeliness, cost, access, and patient outcomes in defined populations.