To give the system its smarts, the researchers trained it using 129,450 close-up images of skin lesions covering more than 2,000 different diseases, providing a vast database of examples to learn from.
Next, the team borrowed an algorithm developed by Google to spot the difference between cats and dogs in images, and adapted it to tell the difference between skin marks.
They put their new device up against 21 qualified dermatologists, who were shown 376 images of skin lesions and asked to judge if they would refer the patient for further analysis, or give them the all-clear.
Across the board, the AI was able to match the success rate of the professionals.
But the technology isn’t designed to replace doctors – the researchers stress that it’s designed to give people easier access to the first two screening stages before getting expert help.