News: Man against machine. Can AI outperform dermatologists when diagnosing skin cancer?

Typical CNN architecture

According to American Cancer Society key statistics for melanoma skin cancer are as follows:

  • About 91,270 new melanomas will be diagnosed (about 55,150 in men and 36,120 in women).
  • About 9,320 people are expected to die of melanoma (about 5,990 men and 3,330 women).
One of these two lesions is a melanoma. Can you guess which one actually? Source: The methods man

The CNN works like the brain of a child. To train it, we showed the CNN more than 100,000 images of malignant and benign skin cancers and moles and indicated the diagnosis for each image. Only dermoscopic images were used, that is lesions that were imaged at a 10-fold magnification. With each training image, the CNN improved its ability to differentiate between benign and malignant lesions.

After finishing the training, we created two test sets of images from the Heidelberg library that had never been used for training and therefore were unknown to the CNN. One set of 300 images was built to solely test the performance of the CNN. Before doing so, 100 of the most difficult lesions were selected to test real dermatologists in comparison to the results of the CNN.

The CNN missed fewer melanomas, meaning it had a higher sensitivity than the dermatologists, and it misdiagnosed fewer benign moles as malignant melanoma, which means it had a higher specificity; this would result in less unnecessary surgery.

Check this video for the information regarding the first signs of a melanoma.

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Blockchain infrastructure aimed to host, train and use artificial intelligence (AI) in healthcare. Our website: https://skychain.global/

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