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The role of technology in melanoma screening and diagnosis.

Albert T YoungNiki B VoraJose CortezAndrew TamYildiray YeniayLadi AfifiDi YanAdi NosratiAndrew WongArjun JohalMaria L Wei
Published in: Pigment cell & melanoma research (2020)
Melanoma presents challenges for timely and accurate diagnosis. Expert panels have issued risk-based screening guidelines, with recommended screening by visual inspection. To assess how recent technology can impact the risk/benefit considerations for melanoma screening, we comprehensively reviewed non-invasive visual-based technologies. Dermoscopy increases lesional diagnostic accuracy for both dermatologists and primary care providers; total body photography and sequential digital dermoscopic imaging also increase diagnostic accuracy, are supported by automated lesion detection and tracking, and may be best suited to use by dermatologists for longitudinal follow-up. Specialized imaging modalities using non-visible light technology have unproven benefit over dermoscopy and can be limited by cost, access, and training requirements. Mobile apps facilitate image capture and lesion tracking. Teledermatology has good concordance with face-to-face consultation and increases access, with increased accuracy using dermoscopy. Deep learning models can surpass dermatologist accuracy, but their clinical utility has yet to be demonstrated. Technology-aided diagnosis may change the calculus of screening; however, well-designed prospective trials are needed to assess the efficacy of these different technologies, alone and in combination to support refinement of guidelines for melanoma screening.
Keyphrases
  • deep learning
  • skin cancer
  • primary care
  • high resolution
  • machine learning
  • palliative care
  • clinical practice
  • artificial intelligence
  • mass spectrometry
  • high throughput
  • loop mediated isothermal amplification