Artificial Intelligence and Dermatology

<p>Would you trust a machine to diagnose your skin cancer? Or, maybe, to reassure you that a mole is “ok”? We take a dive into the world of machine learning, which is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. The most promising advances in medical image analysis have used a type of algorithm known as a deep neural network. But what happens if the images aren’t of good enough quality?</p> <p>We discuss both the great potential and also some of the current limitations of work in this area being done on both sides of the Atlantic, with <a href='https://uk.linkedin.com/in/dr-colin-morton-946489206'>Dr Colin Morton</a>, who is a consultant dermatologist in NHS Forth Valley and is <a href='https://www.woshealthinnovation.scot/exemplar-projects/artificial-intelligence-skin-cancer-consortium/'>clinical operational lead for a skin cancer AI consortium in Scotland</a>, <a href='https://www.mayoclinic.org/biographies/davis-mark-denis-p-m-d/bio-20053324'>Professor Mark Davis</a> and <a href='https://www.mayo.edu/research/faculty/murphree-dennis-h-jr-ph-d/bio-20481774'>Dr Dennis Murphree</a>, the Director of Digital Health and Artificial Intelligence in Dermatology at the Mayo clinic, Rochester, Minnesota, USA.</p> <p><a href='https://www.dundee.ac.uk/stories/artificial-intelligence-help-diagnose-skin-cancers'>Artificial Intelligence to help diagnose skin cancers: NHS Tayside project</a></p> <p><a href='https://newsnetwork.mayoclinic.org/discussion/embracing-the-transformative-power-of-digital-pathology/'>Embracing the transformative power of digital pathology: Mayo Clinic</a></p> <p><a href='https://www.nature.com/news/can-we-open-the-black-box-of-ai-1.20731'>Can we open the black box of AI?</a></p> <p><a href='https://pubmed.ncbi.nlm.nih.gov/32434009/'>Deep learning for dermatologists Part 1</a>  <a href='https://pubmed.ncbi.nlm.nih.gov/32428608/'>Part 2</a></p>