An Artificial Intelligence (AI) system has been found to detect skin cancer more accurately than a group of experienced dermatologists from 17 countries around the world, a study said on Tuesday.
In the experiment, the team of researchers from Germany, France and the US trained a form of AI or Machine Learning known as a deep learning convolutional neural network (CNN) to identify skin cancer by showing it more than 100,000 images of malignant melanomas — the most lethal form of skin cancer — as well as harmless moles.
When its performance was compared with that of 58 international dermatologists, the CNN missed fewer melanomas and misdiagnosed benign moles less often as malignant than the group of dermatologists, showed the findings published in the journal Annals of Oncology.
“The CNN works like the brain of a child. To train it, we showed the CNN more than 100,000 images of malignant and benign skin cancers and moles and indicated the diagnosis for each image,” said first author of the study Professor Holger Haenssle from the University of Heidelberg in Germany.
“Only dermoscopic images were used, that is lesions that were imaged at a 10-fold magnification. With each training image, the CNN improved its ability to differentiate between benign and malignant lesions,” Haenssle added.
A CNN is an artificial neural network inspired by the biological processes at work when nerve cells (neurons) in the brain are connected to each other and respond to what the eye sees.
The CNN is capable of learning fast from images that it “sees” and teaching itself from what it has learned to improve its performance — a process known as Machine Learning.
“These findings show that deep learning convolutional neural networks are capable of out-performing dermatologists, including extensively trained experts, in the task of detecting melanomas,” Haenssle said.
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.
It can be cured if detected early, but many cases are only diagnosed when the cancer is more advanced and harder to treat.
But despite the promising results from the experiment, the researchers do not envisage that the CNN would take over from dermatologists in diagnosing skin cancers, but that it could be used as an additional aid.
“This CNN may serve physicians involved in skin cancer screening as an aid in their decision whether to biopsy a lesion or not,” Haenssle said. (IANS)