An Inspectable Vision-Language and Convolutional Ensemble for Facial Pigmented Lesion Diagnosis

This publication has 23 references indexed in Scilit:

• A multimodal vision foundation model for clinical dermatology
  Nature Medicine, 2025
• BCN20000: Dermoscopic Lesions in the Wild
  Scientific Data, 2024
• Transparent medical image AI via an image–text foundation model grounded in medical literature
  Nature Medicine, 2024
• Ensembles of Deep Convolutional Neural Networks for Detecting Melanoma in Dermoscopy Images
  2021
• Skin lesion classification using ensembles of multi-resolution EfficientNets with meta data
  MethodsX, 2020
• Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task
  European Journal of Cancer, 2019
• Guidelines of care for the management of primary cutaneous melanoma
  Journal of the American Academy of Dermatology, 2019
• The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions
  Scientific Data, 2018
• Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists
  Annals of Oncology, 2018
• Dermatologist-level classification of skin cancer with deep neural networks
  Nature, 2017