What is AI? Applications of artificial intelligence to dermatology

Abstract

Summary In the past, the skills required to make an accurate dermatological diagnosis have required exposure to thousands of patients over many years. However, in recent years, artificial intelligence (AI) has made enormous advances, particularly in the area of image classification. This has led computer scientists to apply these techniques to develop algorithms that are able to recognize skin lesions, particularly melanoma. Since 2017, there have been numerous studies assessing the accuracy of algorithms, with some reporting that the accuracy matches or surpasses that of a dermatologist. While the principles underlying these methods are relatively straightforward, it can be challenging for the practising dermatologist to make sense of a plethora of unfamiliar terms in this domain. Here we explain the concepts of AI, machine learning, neural networks and deep learning, and explore the principles of how these tasks are accomplished. We critically evaluate the studies that have assessed the efficacy of these methods and discuss limitations and potential ethical issues. The burden of skin cancer is growing within the Western world, with major implications for both population skin health and the provision of dermatology services. AI has the potential to assist in the diagnosis of skin lesions and may have particular value at the interface between primary and secondary care. The emerging technology represents an exciting opportunity for dermatologists, who are the individuals best informed to explore the utility of this powerful novel diagnostic tool, and facilitate its safe and ethical implementation within healthcare systems.

Perceptions and attitudes of medical students regarding artificial intelligence in dermatology

“…Editor, Artificial intelligence (AI) is progressing rapidly, and its application in the field of medicine is increasing. 1 AI algorithms have been shown to be as accurate as dermatologists in classifying various skin diseases based on clinical images. 2,3 Furthermore, AI can assist non-dermatologists in classifying skin conditions.…”

Artificial Intelligence Applications in Dermatology: Where Do We Stand?

“…One of the main limitations to AI is that the decisions made by these technologies are ultimately a reflection of the input data used to train the system (87). This theoretically implies that applications can only be used reliably in populations they were trained to assess.…”

Translational health technology and system schemes: enhancing the dynamics of health informatics

“…Neural networks model combined with data and local social media is utilized successfully in the classification of allergy symptoms. [ 53 ] In the field of dermatology AI has the potential to assist in the diagnostics and at the interface between primary and secondary care [ 54 ]. AI applications serve in clinical practice also in pathology and by robot-assisted surgery, in precision robotic treatment, and in virtual reality-enabled robotics [ 42 , 45 ].…”