INTRODUCTION: With the advancement of digital image analysis, predictive analysis, and machine learning methods, studies have emerged regarding the use of artificial intelligence in imaging tests such as dermoscopy.
OBJECTIVE: Construction, testing, and implementation of an artificial neural network based on characteristics of dermoscopic images.
METHODS: 1949 images of melanocytic nevi and melanomas were included, both from the authors’ files and from dermoscopic image banks available on the internet, and routines and plugins were developed to extract 58 features applied to a multilayered neural network construction algorithm. Also, 52 dermatologists assessed 40 random images and compared the results compared.
RESULTS: The training and testing of the neural network obtained a correct percentage of classification of 78.5% and 79.1%, respectively, with a ROC curve covering 86.5% of the area. The sensitivity and specificity of dermatologists were 71.8% and 52%. For the same images and a cutoff point of 0.4 (40%) of the output value, the application obtained 62% and 56% values, respectively.
CONCLUSIONS: Multilayer neural network models can assist in the dermoscopic evaluation of melanocytic nevi and melanomas regarding the differential diagnosis between them.

Keywords: Artificial intelligence; Diagnosis; Melanoma; Nevus

Melanoma is a rare neoplasm in the pediatric population, and it is even rarer in children under 10 years of age. Total body mapping constitutes a low-cost and non-invasive method that increases diagnostic accuracy in evaluating pigmented lesions, especially in high-risk patients. We reported the case of a 9-year boy with dysplastic nevus syndrome, in which one lesion presented a subtle change (asymmetry of structures) within a 6-months follow-up. Its excision resulted in melanoma with a Breslow thickness of 1 mm and a negative sentinel lymph node. Total body mapping reduces the number of unnecessary excisions. It allows diagnosis of melanomas in early and potentially curable stages, especially in children and patients with risk factors such as dysplastic nevus syndrome. We report this case due to the rarity of the neoplasia in this age group and also to demonstrate the importance of sequential digital dermoscopy in early diagnosis of melanoma in this population.

Keywords: Dermoscopy; Melanoma; Dysplastic nevus syndrome

Blue nevus is a benign lesion arising from dermal melanocytes containing large amounts of melanin. The agminated variant presents a cluster of blue nevus lesions with linear or blaschkoid distribution. We report two cases of patients with agminated blue nevus that developed on previous acne scars, and dermoscopy helped a lot in the differential diagnosis. This is the first occurrence found in the literature of agminated blue nevus that appeared on a previous scar, which may have occurred by chance or as a result of the collagen remodeling process inherent to the healing process.

Keywords: Scar; Collagen; Dermoscopy; Nevus blue