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Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study.

Roman Christoph MaronJochen Sven UtikalAchim HeklerAxel HauschildElke C SattlerWiebke SondermannSebastian HaferkampBastian SchillingMarkus Vincent HepptPhilipp JansenMarkus ReinholzCindy FranklinLaurenz SchmittDaniela HartmannEva Krieghoff-HenningMax SchmittMichael WeichenthalChristof von KalleStefan FröhlingTitus Josef Brinker
Published in: Journal of medical Internet research (2020)
The findings of our study show that AI support can improve the overall accuracy of the dermatologists in the dichotomous image-based discrimination between melanoma and nevus. This supports the argument for AI-based tools to aid clinicians in skin lesion classification and provides a rationale for studies of such classifiers in real-life settings, wherein clinicians can integrate additional information such as patient age and medical history into their decisions.
Keyphrases
  • artificial intelligence
  • deep learning
  • machine learning
  • big data
  • skin cancer
  • healthcare
  • case report
  • cross sectional
  • soft tissue
  • health information
  • basal cell carcinoma