How Machine Learning Technology Detects Skin Cancer

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Over the past years, SkinVision has made great progress towards developing an application that is significantly reliable in recognizing dangerous skin lesions.

SkinVision started off with a ‘rule-based’ system which went through every picture and checked skin lesions for certain characteristics to determine risk. Even though this algorithm has helped us detect the risk of thousands of dangerous lesions, we are continuously looking to improve its accuracy.

That is why we are very excited to announce that in January 2018 we introduced a smart system that detects dangerous skin lesions completely based on a machine learning algorithm.

What is Machine Learning? Here is a great animation that explains it in two minutes.

Courtesy of Oxford Sparks

How is Machine Learning used in the SkinVision application?

We have trained the SkinVision algorithm with large quantities of images which were previously assessed by our team of dermatologists.

The algorithm learns which lesions are dangerous and which ones are not. We continuously train and improve our algorithm with new sets of images. From now on, all the pictures submitted through the SkinVision application go through this algorithm.

It is common for doctors to ask a second opinion, and so at this moment, every photo is also reviewed by our in-house dermatologists and image recognition experts. We have set up this process to assist the algorithm to become more accurate and to make sure that our dermatologists agree with the risk indication.

The best part, however, is that we are training our algorithm to become on a par with the best dermatologists.

Every photo of skin spots makes our algorithm smarter at detecting skin cancer risk. Contribute to our mission of saving lives by using SkinVision.

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"The melanoma could have been on my arm for years"
Andrew Bartlett
United Kingdom
"The melanoma could have been on my arm for years"
Andrew Bartlett
United Kingdom

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