A dataset of skin lesion images collected in Argentina for the evaluation of AI tools in this population.
María Agustina Ricci LaraMaría Victoria Rodríguez KowalczukMaite Lisa ElicecheMaría Guillermina FerraressoDaniel Roberto LunaSonia Elizabeth BenitezLuis Daniel MazzuoccoloPublished in: Scientific data (2023)
In recent years, numerous dermatological image databases have been published to make possible the development and validation of artificial intelligence-based technologies to support healthcare professionals in the diagnosis of skin diseases. However, the generation of these datasets confined to certain countries as well as the lack of demographic information accompanying the images, prevents having a real knowledge of in which populations these models could be used. Consequently, this hinders the translation of the models to the clinical setting. This has led the scientific community to encourage the detailed and transparent reporting of the databases used for artificial intelligence developments, as well as to promote the formation of genuinely international databases that can be representative of the world population. Through this work, we seek to provide details of the processing stages of the first public database of dermoscopy and clinical images created in a hospital in Argentina. The dataset comprises 1,616 images corresponding to 1,246 unique lesions collected from 623 patients.
Keyphrases
- artificial intelligence
- deep learning
- big data
- convolutional neural network
- healthcare
- machine learning
- adverse drug
- end stage renal disease
- chronic kidney disease
- mental health
- ejection fraction
- newly diagnosed
- soft tissue
- peritoneal dialysis
- optical coherence tomography
- wound healing
- prognostic factors
- systematic review
- emergency department
- randomized controlled trial
- mouse model
- health information
- electronic health record