Deep neural networks are superior to dermatologists in melanoma image classification.

Deep neural networks are superior to dermatologists in melanoma image classification.

Publication date: Aug 08, 2019

Melanoma is the most dangerous type of skin cancer but is curable if detected early. Recent publications demonstrated that artificial intelligence is capable in classifying images of benign nevi and melanoma with dermatologist-level precision. However, a statistically significant improvement compared with dermatologist classification has not been reported to date.

For this comparative study, 4204 biopsy-proven images of melanoma and nevi (1:1) were used for the training of a convolutional neural network (CNN). New techniques of deep learning were integrated. For the experiment, an additional 804 biopsy-proven dermoscopic images of melanoma and nevi (1:1) were randomly presented to dermatologists of nine German university hospitals, who evaluated the quality of each image and stated their recommended treatment (19,296 recommendations in total). Three McNemar’s tests comparing the results of the CNN’s test runs in terms of sensitivity, specificity and overall correctness were predefined as the main outcomes.

The respective sensitivity and specificity of lesion classification by the dermatologists were 67.2% (95% confidence interval [CI]: 62.6%-71.7%) and 62.2% (95% CI: 57.6%-66.9%). In comparison, the trained CNN achieved a higher sensitivity of 82.3% (95% CI: 78.3%-85.7%) and a higher specificity of 77.9% (95% CI: 73.8%-81.8%). The three McNemar’s tests in 2 cD7 2 tables all reached a significance level of p

Brinker, T.J., Hekler, A., Enk, A.H., Berking, C., Haferkamp, S., Hauschild, A., Weichenthal, M., Klode, J., Schadendorf, D., Holland-Letz, T., von Kalle, C., Fr”ohling, S., Schilling, B., and Utikal, J.S. Deep neural networks are superior to dermatologists in melanoma image classification. 23718. 2019 Eur J Cancer (119):

Concepts Keywords
Artificial Intelligence Artificial intelligence
Benign Neural network
Biopsy Cancer
CNN Nevus
Confidence Interval Medicine
Convolutional Neural Network RTT
Deep Learning Organ systems
Deep Neural Networks Dermatology
Dermatologist Melanoma
Image Classification Images melanoma nevi
Lesion Deep neural networks
Melanoma Convolutional neural network
Nevi

Semantics

Type Source Name
disease MESH nevi
disease DOID skin cancer
disease MESH skin cancer
pathway BSID Melanoma
disease MESH melanoma
disease DOID melanoma

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