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[2 min read] Accuracy of computer-aided melanoma diagnosis | Prof David Wilkinson
This month, I was fascinated to read a meta-analysis of the accuracy of computer-aided melanoma diagnosis, by Vincent Dick et al.
As we all know, computer-aided diagnosis is becoming more common across many aspects of medicine, including dermatology and skin cancer. We have heard about recent studies that use artificial intelligence and machine learning to achieve very high rates of diagnostic accuracy.
The current study is a useful summary, showing (as so many such meta-analyses do) that many studies done to date are of poor or limited quality, and that only a small number are of sufficient quality to be considered reliable.
This report shows sensitivity around 75% and specificity around 85% for melanoma diagnosis, and equivalent accuracy with dermatologists’ diagnosis.
As we move into a new era of computer-aided skin cancer diagnosis, researchers need to ensure that the studies they do reflect real-world practice.
Professor David Wilkinson
Read more from Professor David Wilkinson on recent research:
- Dysplastic naevi genetic makeup
- What to do when a partial biopsy of a suspected melanoma is performed
- Artificial Intelligence in clinical practice
- Prof David Wilkinson on melanoma guidelines: Dermoscopy
- How will artificial intelligence benefit GPs in skin cancer medicine?
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