Deep Learning Network can Diagnose Skin Cancer Better Than Dermatologists

The scientists said on Tuesday that a computer or artificial intelligence (AI) proved to be better than human experienced dermatologists at detecting skin cancer in patients. In order to teach the artificial neural network how to identify skin cancer, the researchers fed it a dataset of over 100,000 images of malignant melanomas and benign moles.

The diagnostic credibility of the artificial intelligence system was compared to that of 58 dermatologists from 17 countries, including Greece. In a technique known as machine learning, the device was able to quickly evaluate information researchers presented it, and improve its ability to pinpoint skin cancers. Four weeks after making the level I assessment, each participant was asked to review their diagnosis at level II, where they were given far more information about the patient - including age, sex, and the location of the lesion, as well as magnified images of the same case.

Aadi Kalloo, an author of the study and senior data analyst at New York's Memorial Sloan Kettering Cancer Center, contends that "a human definitely always needs to be in the loop" when diagnosing skin cancer, adding that the CNN's diagnostic performance was superior to most, but not all, dermatologists. The computer was also less likely to misdiagnose a Benign Mole as Malignant.

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Melanoma incidents are constantly increasing, with about 232,000 new diagnoses and 55,500 deaths each year worldwide.

On average, the dermatologists correctly detected around 86.6 percent of melanomas while the CNN identified 95 percent of them.

Malignant melanoma is the most deadly type of skin cancer. Haenssle said that the findings show that "deep learning convolutional neural networks are capable of out-performing dermatologists, including extensively trained experts, in the task of detecting melanomas". The condition is treatable when caught soon enough, but is all too often diagnosed when the cancer is more advanced and harder to treat.

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Matthew Gass, from the British Association of Dermatologists, said: "Skin cancer is the most common cancer in the United Kingdom so it is very exciting to see emerging technologies that can aid in the diagnosis of this disease".

"Currently, there is no substitute for a thorough clinical examination", experts Victoria Mar from Monash University in Melbourne and Peter Soyer of the University of Queensland wrote in an editorial published with the study.

The machine is called CNN - deep learning convolutional neural network.

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