In dermatology, the past year and so have been marked by breakthroughs in machine learning.This has made automated diagnosis of some cutaneous lesions achievable, comments and article in JAMA Dermatology by George A. Zakhem, BS; Catherine C. Motosko, BS; Roger S. Ho, MD, MS, MPH.

Although machine learning systems have been around since the 1950s, the past decade has seen an unprecedented surge in their adoption. This rise in artificial intelligence can be attributed to an explosion in the generation of digital data, improvements in algorithms, and substantial advances in computing hardware. As building routines are increasingly routine, they are now used on almost every technological platform we use daily and underlie a range of functions, including speech transcription, recommender systems, and image recognition.

Algorithms for classification

Algorithms have been developed to approach dermatologist-level classification of skin tumors.These technologies show tremendous promise for the improvement of skin cancer screening. Still, many aspects of their use have yet to be elucidated.

One of the models developed by Han et al has been optimized for mobile use and can be accessed without subscription or login (http://modelderm.com/) - the photo above. However, it is still unclear whether the site is designed for patients, nonspecialist clinicians or dermatologists.

You can read the whole article HERE.