Health Care

Artificial Intelligence Outperforms Dermatologist in Melanoma Diagnosis May 29, 2018

Artificial Intelligence Outperforms Dermatologist in Melanoma Diagnosis May 29, 2018

A computer was taught to recognize signs of skin cancer after being shown more than 100,000 images of Melanoma. Some 30 of the dermatologists involved in the study were considered experts as they had more than five years' experience, while 11 had between two to five and 17 had less than two. Four weeks later, the researchers gave the dermatologists clinical information about the patient, including age, sex, and the position of the lesion, and close-up images of the same cases.

First author of the study, Professor Holger Haenssle, senior managing physician at the department of dermatology at the University of Heidelberg in Germany, said: 'The CNN works like the brain of a child.

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

There are about 232,000 new cases of melanoma, and 55,500 deaths, in the world each year, they added.

A team of American, German, and French scientists has created an artificial intelligence that detects skin cancer based on imaging of the skin.

Computers are better than experienced doctors at spotting skin cancer, a new study reveals. Doctors were in an "artificial setting", the test set did not include the full range of skin lesions; and there were fewer images from non-Caucasian skin types and genetic backgrounds to examine.

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Clinicians make better diagnoses with more context. It was shown photos of benign moles and malignant melanomas. Most dermatologists already use digital dermoscopy systems to image and store lesions for documentation and follow-up. At level I, the only information that the dermatologists had at their disposal was from dermoscopic images.

Researchers mentioned such know-how could possibly be used to display screen for pores and skin most cancers, which means circumstances could possibly be recognized far earlier.

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.

The number of skin cancer cases missed by the CNN were fewer than those gone unnoticed by dermatologists, indicating a higher sensitivity.

"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.

In some parts of the body - fingers, toes or scalp, melanoma is hard to image, and AI can not easily recognize atypical lesions of the skin. Others came from countries such as Switzerland, Australia, Japan, and Argentina.