There has been growing scientific interest in the research field of deep learning techniques applied to skin cancer diagnosis in the last decade. Though encouraging data have been globally reported, several discrepancies have been observed in terms of study methodology, result presentations and validation in clinical settings. The present review aimed to screen the scientific literature on the application of DL techniques to dermoscopic melanoma/nevi differential diagnosis and extrapolate those original studies adequately by reporting on a DL model, comparing them among clinicians and/or another DL architecture. The second aim was to examine those studies together according to a standard set of statistical measures, and the third was to provide dermatologists with a comprehensive explanation and definition of the most used artificial intelligence (AI) terms to better/further understand the scientific literature on this topic and, in parallel, to be updated on the newest applications in the medical dermatologic field, along with a historical perspective. After screening nearly 2000 records, a subset of 54 was selected. Comparing the 20 studies reporting on convolutional neural network (CNN)/deep convolutional neural network (DCNN) models, we have a scenario of highly performant DL algorithms, especially in terms of low false positive results, with average values of accuracy (83.99%), sensitivity (77.74%), and specificity (80.61%). Looking at the comparison with diagnoses by clinicians (13 studies), the main difference relies on the specificity values, with a +15.63% increase for the CNN/DCNN models (average specificity of 84.87%) compared to humans (average specificity of 64.24%) with a 14,85% gap in average accuracy; the sensitivity values were comparable (79.77% for DL and 79.78% for humans). To obtain higher diagnostic accuracy and feasibility in clinical practice, rather than in experimental retrospective settings, future DL models should be based on a large dataset integrating dermoscopic images with relevant clinical and anamnestic data that is prospectively tested and adequately compared with physicians.

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In the present study, we employed the ddPCR and IHC techniques to assess the prevalence and roles of RAS and RAF mutations in a small batch of melanoma (n = 22), benign moles (n = 15), and normal skin samples (n = 15). Mutational screening revealed the coexistence of BRAF and NRAS mutations in melanomas and nevi and the occurrence of NRAS G12/G13 variants in healthy skin. All investigated nevi had driver mutations in the BRAF or NRAS genes and elevated p16 protein expression, indicating cell cycle arrest despite an increased mutational burden. BRAF V600 mutations were identified in 54% of melanomas, and NRAS G12/G13 mutations in 50%. The BRAF mutations were associated with the Breslow index (BI) (p = 0.029) and TIL infiltration (p = 0.027), whereas the NRAS mutations correlated with the BI (p = 0.01) and the mitotic index (p = 0.04). Here, we demonstrate that the \"young\" ddPCR technology is as effective as a CE-IVD marked real-time PCR method for detecting BRAF V600 hotspot mutations in tumor biopsies and recommend it for extended use in clinical settings. Moreover, ddPCR was able to detect low-frequency hotspot mutations, such as NRAS G12/G13, in our tissue specimens, which makes it a promising tool for investigating the mutational landscape of sun-damaged skin, benign nevi, and melanomas in more extensive clinical studies.

Atypical clinical and dermoscopic findings, or changes in pigmented melanocytic lesions located on body areas treated with lasers or intense pulsed light (IPL) for hair removal (photoepilation), have been described in the literature. There are three prospective studies in a total of 79 individuals with 287 melanocytic nevi and several case reports reporting the dermoscopic findings and changes after photoepilation. Clinical changes have been reported in 20-100% of individuals, while dermoscopic changes have been observed in 48% to 93% of nevi. More frequent dermoscopic changes included bleaching, the development of pigmented globules, and irregular hyperpigmented areas and regression structures, including gray areas, gray dots/globules, and whitish structureless areas. The diagnostic approach for pigmented lesions with atypical dermoscopic findings and changes after photo-epilation included reflectance confocal microscopy, sequential digital dermoscopy follow-up, and/or excision and histopathology. Challenges pertaining to these diagnostic steps in the context of photoepilation include the detection of findings that may warrant a biopsy to exclude melanoma (ugly duckling, irregular hyperpigmented areas, blue-gray or white areas, and loss of pigment network), the potential persistence of changes at follow-up, and that a histopathologic diagnosis may not be possible due to the distortion of melanocytes or complete regression of the lesion. Furthermore, these diagnostic approaches can be time-consuming, require familiarization of the physician with dermoscopic features, may cause anxiety to the individual, and highlight that avoiding passes of the laser or IPL devices over pigmented lesions is key.

BACKGROUND: Skin cancer diagnostics is challenging, and mastery requires extended periods of dedicated practice.
OBJECTIVE: The aim of the study was to determine if self-paced pattern recognition training in skin cancer diagnostics with clinical and dermoscopic images of skin lesions using a large-scale interactive image repository (LIIR) with patient cases improves primary care physicians\' (PCPs\') diagnostic skills and confidence.
METHODS: A total of 115 PCPs were randomized (allocation ratio 3:1) to receive or not receive self-paced pattern recognition training in skin cancer diagnostics using an LIIR with patient cases through a quiz-based smartphone app during an 8-day period. The participants\' ability to diagnose skin cancer was evaluated using a 12-item multiple-choice questionnaire prior to and 8 days after the educational intervention period. Their thoughts on the use of dermoscopy were assessed using a study-specific questionnaire. A learning curve was calculated through the analysis of data from the mobile app.
RESULTS: On average, participants in the intervention group spent 2 hours 26 minutes quizzing digital patient cases and 41 minutes reading the educational material. They had an average preintervention multiple choice questionnaire score of 52.0% of correct answers, which increased to 66.4% on the postintervention test; a statistically significant improvement of 14.3 percentage points (P<.001; 95% CI 9.8-18.9) with intention-to-treat analysis. Analysis of participants who received the intervention as per protocol (500 patient cases in 8 days) showed an average increase of 16.7 percentage points (P<.001; 95% CI 11.3-22.0) from 53.9% to 70.5%. Their overall ability to correctly recognize malignant lesions in the LIIR patient cases improved over the intervention period by 6.6 percentage points from 67.1% (95% CI 65.2-69.3) to 73.7% (95% CI 72.5-75.0) and their ability to set the correct diagnosis improved by 10.5 percentage points from 42.5% (95% CI 40.2%-44.8%) to 53.0% (95% CI 51.3-54.9). The diagnostic confidence of participants in the intervention group increased on a scale from 1 to 4 by 32.9% from 1.6 to 2.1 (P<.001). Participants in the control group did not increase their postintervention score or their diagnostic confidence during the same period.
CONCLUSIONS: Self-paced pattern recognition training in skin cancer diagnostics through the use of a digital LIIR with patient cases delivered by a quiz-based mobile app improves the diagnostic accuracy of PCPs.
BACKGROUND: ClinicalTrials.gov NCT05661370; https://classic.clinicaltrials.gov/ct2/show/NCT05661370.

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BACKGROUND: Although the role of melanoma risk factors is well documented, their correlation with patients\' age is less frequently analyzed.
METHODS: The analysis was performed among 189 melanoma patients in different age groups, including <30 years, 31-60 years, and >60 years, to investigate the risk factors, topography, and coexistence of morphological features of 209 melanomas (dermoscopic and histopathological).
RESULTS: Among the youngest age group, no correlation with the presence of estimated risk factors was found. The most common dermoscopic pattern was spitzoid and multicomponent asymmetric. The group of middle-aged patients was the most diverse in terms of the occurrence of risk factors, solar lentiginosis, dermoscopic patterns, topography, histological subtypes, and invasiveness of melanomas. The oldest group characterized a strong correlation between solar lentiginosis, NMSC comorbidity, the prevalence of facial melanomas, the dermoscopic pattern of melanoma arising on chronic sun-damaged skin, and regression.
CONCLUSIONS: The findings regarding the presence of age-specific features in melanoma patients, especially in the youngest and middle-aged groups, might be helpful for clinicians and to target secondary prevention efforts.

UNASSIGNED: Oral melanocytic nevi are infrequent oral lesions derived from nevus cells of oral mucosa which causes focal hyperpigmentation. The most common site of occurrence of oral nevi is the hard palate followed by buccal mucosa and gingiva. The mean age group affected are in their 3rd and 4th decade of life and there seems to be a predilection for females. Clinically, oral nevi are usually small, well-circumscribed macules but can also present as slightly raised papules. Histologically, nevi can be classified as Junctional, Compound or Intramucosal, with intramucosal being the more common type in the oral cavity.
UNASSIGNED: In this paper, we report a case of intramucosal nevus in a 25-year-old female patient. The lesion presented as a gingival enlargement in the mandibular anterior region involving the marginal and attached gingiva, which is an extremely rare presentation. The clinical findings, histologic features and surgical management are presented. The patient was followed up for one year and the one year follow up revealed a small area of focal hyperpigmentation at the site of the previous lesion which is being closely monitored.
UNASSIGNED: Nevi located in the mucous membrane have been documented to pose a threat of malignant transformation. Hence, all pigmented lesions of the oral cavity should be cautiously diagnosed.

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