Health Care

Without Context, a Neural Network Diagnosed Melanoma Better Than 58 Dermatologists

Without Context, a Neural Network Diagnosed Melanoma Better Than 58 Dermatologists

Scientists from Germany, the United States and France developed an artificial intelligence system to distinguish unsafe skin lesions from benign ones, showing it more than 100,000 images.

For the study, a team of researchers from Germany, the US and France trained an AI system to identify skin cancer using 100,000-plus images, including images of malignant melanomas and benign moles.

After training the CNN to recognise the differing forms of skin cancer, the researchers pitted it against that of 58 global dermatologists.

"When dermatologists received more clinical information and images at level II, their diagnostic performance improved", Haenssle said.

The laptop was extra correct even in comparison with essentially the most skilled medical doctors, the research, printed within the Annals of Oncology, discovered. When provided with clinical information and close-up images of the cases, the dermatologists were able to accurately diagnose 88.9 percent of malignant melanomas and 75.7 percent of benign moles.

The incidence of malignant melanoma is increasing, with an estimated 232,000 new cases worldwide and around 55,500 deaths from the disease each year [3]. This is why this CNN is so impressive - it would be able to identify more cancers early on, thereby saving lives. Doctors correctly found skin cancer and benign moles 86.6 percent of the time, but CNN was correct 95 percent of the time.

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Malignant melanoma is essentially the most lethal sort of pores and skin most cancers. About 19% had their years of experience ranging from two to five years while the remaining 29% were new doctors with less than two years of working experience in the field.

"When I came across recent reports on deep-learning algorithms that outperform human experts in specific tasks, I immediately knew that we had to explore these artificial intelligence algorithms for diagnosing melanoma", Holger Haenssle of Germany's University of Heidelberg said.

However, the AI is a good tool to diagnose skin cancer fast and easy.

More research needs to be carried out ensure the CNN is accurate when diagnosing areas hard to image such as the fingers, toes and scalp, and to train it to pick up unusual melanomas, as well as lesions that patients haven't yet found. The authors said dermatologists shouldn't worry about their positions, though-this finding will likely serve as a diagnostic aid rather than a replacement.

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


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