{"id":178780,"date":"2021-02-15T16:56:56","date_gmt":"2021-02-15T13:56:56","guid":{"rendered":"https:\/\/en.buradabiliyorum.com\/this-ai-can-assess-skin-melanoma-as-accurately-as-human-dermatologists\/"},"modified":"2021-02-15T16:56:56","modified_gmt":"2021-02-15T13:56:56","slug":"this-ai-can-assess-skin-melanoma-as-accurately-as-human-dermatologists","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/this-ai-can-assess-skin-melanoma-as-accurately-as-human-dermatologists\/","title":{"rendered":"#This AI can assess skin melanoma as accurately as human dermatologists"},"content":{"rendered":"

“#This AI can assess skin melanoma as accurately as human dermatologists<\/strong>”
\n<\/p>\n

\n Scientists from the University of Gothenburg have developed an algorithm that assesses the severity of skin melanoma as accurately as dermatologists.<\/p>\n

The system was developed to help doctors determine the stage that a skin cancer has reached.<\/p>\n

While patients often independently find melanomas by spotting a new mole or a change in an existing one, even dermatologists\u00a0can struggle to decide whether it\u2019s invasive or not.<\/p>\n

The researchers suspected that AI could assist them with the task.<\/p>\n

[Read:\u00a0How Polestar is using blockchain to increase transparency]<\/em><\/p>\n

They classified the\u00a0melanomas<\/span>\u00a0with a convolutional neural network (CNN), a powerful method of analyzing images that\u2019s proven adept<\/a>\u00a0at identifying different\u00a0skin lesions.<\/p>\n

The researchers trained and validated the CNN on 937 images of melanomas collected through a dermascope, a handheld instrument used to examine the skin.<\/p>\n

They then tested the algorithm\u2019s evaluations on 200 cases that had been diagnosed by a\u00a0dermatopathologist.<\/span><\/p>\n

When they compared its performance to the analysis of seven independent dermatologists, the result was a draw.<\/p>\n

\u201cNone of the dermatologists significantly outperformed the ML algorithm,\u201d said<\/a> study author Sam Polesie.<\/p>\n

The researchers acknowledge that the algorithm still needs further refinement and longer-term evaluation in a clinical setting.<\/p>\n

However, their study shows that AI could help assess the\u00a0severity of melanoma before surgery, which affects how extensive an operation needs to be.<\/p>\n

You can read a pre-proof of the study paper in the Journal of the American Academy of Dermatology<\/a><\/em>.<\/p>\n

\n Published February 15, 2021 \u2014 13:56 UTC\n <\/p>\n<\/p><\/div>\n