The diagnostic credibility of the artificial intelligence system was compared to that of 58 dermatologists from 17 countries, including Greece.
The number of skincancer cases missed by the CNN were fewer than those gone unnoticed by dermatologists, indicating a higher sensitivity.
While dermatologists' performance did improve, he said, the physicians couldn't keep up with the CNN, which continued to outperform those doctors' diagnostic abilities in each case. The new study, published in the Annals of Oncology, was accompanied by a commentary that ponders that very question. They added most dermatologists were already using digital dermoscopy systems and other such tools for cancer-related documentation, detection, and follow-up of patients.
On average, dermatologists put the correct diagnosis at 86.6% of cases, while CNN - in 95% of cases. A Google algorithm devised to recognise unusual moles not only picked up more cancers but also ruled out more benign lesions.
Although machines doctors are still a thing of science-fiction, a team of medical researchers from Germany proved that artificial intelligence could outperform human diagnosticians. 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.
The hope is that the technology could eventually be implemented as a way to diagnose skin cancer in its early days before it spreads.
"Today, nothing can replace a thorough clinical examination", stated Victoria Mar and Peter Soyer, two renowned Australian dermatology professors, in the report that accompanied the study.
They highlight a number of issues that would need to be addressed before AI could become standard in clinics, including the difficulty of imaging some melanomas on sites such as the fingers, toes and scalp, and how to train AI sufficiently to recognise atypical melanomas and ones that patients are unaware of.
A type of machine learning called a convolutional neural network was trained...
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