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Artificial Intelligence Outperforms Doctors in Diagnosing Skin Cancer
Researchers developed a new artificial intelligence (AI) tool known as a deep learning convolutional neural network (CNN), and found it is able to diagnose skin cancer (specifically melanoma) more accurately than a group of 58 international dermatologists with varying levels of expertise.
Study in a Sentence: Researchers developed a new artificial intelligence (AI) tool known as a deep learning convolutional neural network (CNN), and found it is able to diagnose skin cancer (specifically melanoma) more accurately than a group of 58 international dermatologists with varying levels of expertise. The tool was created using Google’s AI technology and was trained using 100,000 skin images.
Healthy for Humans: The CNN improved the doctors’ accuracy of diagnosis for skin cancers from a sensitivity of 86.6% to 95% (i.e., the doctors missed fewer true cancerous moles) and from a specificity of 71.3% to 82.5% (i.e., the doctors misdiagnosed fewer non-cancerous moles as cancerous). Hence, the tool can prevent fewer cancer patients from being misdiagnosed as normal early on in their disease progression as well as prevent patients without cancer from undergoing unnecessary diagnostic procedures and treatments.
Redefining Research: This research demonstrates the great potential of AI to be adopted to perform human brain functions and may be used to advance computational models to study brain disorders in the near future.
References
- Haenssle HA, Fink C, Schneiderbauer R, et al. Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists. Ann Oncol. 2018. https://doi.org/10.1093/annonc/mdy166.
