The study compares five pre‑trained convolutional neural networks—ResNet50, VGG16, VGG19, MobileNet, and InceptionV3—for melanoma detection using dermatoscopic and histopathological image datasets. Accuracy varied across models and modalities, with ResNet50 achieving the highest scores (84% on HAM10000 and 83% on CR‑AI4SkIN) and InceptionV3 the lowest (71% on ISIC 2018). The results show that a model’s performance on dermatoscopic images does not necessarily predict its performance on histopathological images.
By Wagner Moreno Schmitz, Marco Antonio de Castro Barbosa, Thiago Magalh\~aes Amaral, Dalcimar Casanova, Jefferson Tales Oliva
arXiv:2411. 16956v2 Announce Type: replace-cross Abstract: As global life expectancy increases, so does the burden of chronic diseases, yet individuals exhibit considerable variability in the rate at which they age.
By Kaustubh Chakradeo (University of Copenhagen, Section of Epidemiology, Department of Public Health, Copenhagen, Denmark), Pernille Nielsen (Technical University of Denmark, Department of Applied Mathematics and Computer Science, Denmark), Lise Mette Rahbek Gjerdrum (Department of Pathology, Copenhagen University Hospital- Zealand University Hospital, Roskilde, Denmark, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark), Gry Sahl Hansen (Department of Pathology, Copenhagen University Hospital- Zealand University Hospital, Roskilde, Denmark), David A Duch\^ene (University of Copenhagen, Section of Epidemiology, Department of Public Health, Copenhagen, Denmark), Laust H Mortensen (University of Copenhagen, Section of Epidemiology, Department of Public Health, Copenhagen, Denmark, Danmarks Statistik, Denmark), Majken K Jensen (University of Copenhagen, Section of Epidemiology, Department of Public Health, Copenhagen, Denmark), Samir Bhatt (University of Copenhagen, Section of Epidemiology, Department of Public Health, Copenhagen, Denmark, Imperial College London, United Kingdom)
arXiv:2608. 11280v1 Announce Type: cross Abstract: Skin cancer diagnosis from dermoscopic images remains challenging due to high intra-class variability, inter-class similarity, class imbalance, and the limited interpretability of deep learning models.
By Rofiqul Islam, Lilatul Ferdouse
arXiv:2609.07180v1 Announce Type: cross
Abstract: Basal Cell Carcinoma (BCC) is the most common type of skin cancer, accounting for nearly 80% of skin cancer di- agnoses. Its optimal clinical managem...
By Alexandros Papadopoulos, Chrysa Episkopou, Ioannis Sarafis, Aimilios Lallas, Anastasios Delopoulos