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Automated diagnostic instruments for cutaneous melanoma.

Malene E Vestergaard1, Scott W Menzies

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Automated diagnostic instruments for skin melanoma show mixed results. While one device matched human specialists in specificity, others performed significantly worse in real-world clinical settings.

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Area of Science:

  • Dermatology
  • Medical Diagnostics
  • Artificial Intelligence in Medicine

Background:

  • Cutaneous melanoma diagnosis relies heavily on expert human assessment.
  • The development of automated diagnostic instruments aims to improve accuracy and efficiency.
  • Real-world clinical validation is crucial for assessing the utility of these instruments.

Purpose of the Study:

  • To review and discuss evidence on fully automated diagnostic instruments for cutaneous melanoma.
  • To compare the diagnostic accuracy of these instruments against human diagnosis in clinical settings.
  • To evaluate the performance of instruments based on sensitivity and specificity.

Main Methods:

  • Systematic review of studies comparing automated instruments with human diagnosis.
  • Inclusion criteria focused on studies reporting sensitivity and specificity for melanoma on independent test sets.
  • Exclusion of studies not directly comparing diagnostic accuracy or lacking sufficient sample size.

Main Results:

  • Three instruments were evaluated in real-world clinical settings against human diagnosis.
  • Two instruments demonstrated significantly lower specificity for melanoma diagnosis compared to specialists.
  • One instrument achieved equivalent specificity and showed a trend towards superior sensitivity, though not statistically significant.

Conclusions:

  • Current automated diagnostic instruments for cutaneous melanoma present variable performance.
  • Some instruments show inferior diagnostic specificity compared to dermatologists.
  • Further development and rigorous clinical validation are needed for widespread adoption.