AI Better Than Dermatologists at Diagnosing Skin Cancer

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A new artificially intelligent computer can diagnose skin cancer more accurately than doctors, according to researchers.

The artificial intelligence, a so-called convolutional neural network, has managed to be better than dermatologists at spotting skin cancer by simply scanning series of photographs, announced today the research team. Once trained it was tested against 58 dermatologists from across 17 countries, who were shown benign moles and malignant melanomas. Then, four weeks later they were given clinical information about the patient (including age, sex and position of the lesion) and close-up images of the same 100 cases (level II) and asked for diagnoses and management decisions again.

The first author of the study, Professor Holger Haenssle, senior managing physician at the Department of Dermatology, University of Heidelberg, Germany, explained: "The CNN works like the brain of a child".

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The dermatologists accurately detected melanomas in 86.6% of the cases and could correctly identify non-malignant lesions 71% of the time. They also believe there are 232,000 new cases of skin cancer and 55,500 deaths are reported each year.

An worldwide team of researchers from the United States, France, and Germany reportedly taught an AI to determine the difference between unsafe skin lesions and benign ones using over 100,000 images. However, the AI is a good tool to diagnose skin cancer fast and easy. The gap isn't as big as you would think, but the fact that it was able to pick up on skin cancer close to 10% more than regular doctors, it could mean more lives are saved.

The CNN was trained on over 100,000 dermoscopic images. "Irrespective of any physicians' experience, they may benefit from assistance by a CNN's image classification".

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According to the researchers, their deep learning network could one day help dermatologists in screening skin cancer and making the right decision to either biopsy a lesion or not.

In an accompanying editorial [4] Dr Victoria Mar (Monash University, Melbourne, Australia) and Professor H. Peter Soyer (The University of Queensland, Brisbane, Australia) write: "Currently, diagnostic accuracy for melanoma is dependent on the experience and training of the treating doctor". It also missed fewer melanomas, meaning it was more sensitive than the human dermatologists in terms of detection. It will allow doctors to surgically remove them before it starts spreading.

That being said, these impressive results indicate that we're about to experience a paradigm shift, not only in dermatology but in just about every medical field, thanks to developments in artificial intelligence.

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It should be noted that melanomas in some parts of the body, including the fingers, toes, and scalp, are hard to photograph, and the CNN may have difficulty recognizing atypical lesions or ones that patients aren't aware they have.

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