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Advances in Early Detection of Melanoma and the Future of At-Home Testing.

Zachary R GarrisonConnor M HallRosalyn M FeyTerri ClisterNabeela KhanRebecca NicholsRajan P Kulkarni
Published in: Life (Basel, Switzerland) (2023)
The past decade has seen numerous advancements in approaches to melanoma detection, each with the common goal to stem the growing incidence of melanoma and its mortality rate. These advancements, while well documented to increase early melanoma detection, have also garnered considerable criticism of their efficacy for improving survival rates. In this review, we discuss the current state of such early detection approaches that do not require direct dermatologist intervention. Our findings suggest that a number of at-home and non-specialist methods exist with high accuracy for detecting melanoma, albeit with a few notable concerns worth further investigation. Additionally, research continues to find new approaches using artificial intelligence which have promise for the future.
Keyphrases
  • artificial intelligence
  • skin cancer
  • big data
  • machine learning
  • randomized controlled trial
  • risk factors
  • basal cell carcinoma
  • deep learning
  • cardiovascular disease
  • type diabetes
  • cardiovascular events
  • quantum dots