Augmented dermatology is dermatology augmented with artificial intelligence or deep learning algorithms. These algorithms are trained on large datasets of dermoscopic images in order to automate recognition of complex skin patterns and features. Augmented dermatology is developed to help dermatologists identify malignant skin lesions, such as skin cancer, faster.
Augmented dermatology is based on quantitative assessments of dermatological and dermoscopic images. By using advanced scanning parameters, deep learning or computer-aided detection algorithms can study features in these images and learn to recognize them. In this way, skin lesions and structures can be automatically identified.
Dermatologists will transition into a new role, i.e. the role of an augmented dermatologist, where artificial intelligence will expand the dermatologists’ skills and capabilities, so experts become super experts. An augmented dermatologist will be able to take a more holistic approach to treat patients, combining artificially generated findings with additional clinical data from the patient anamnesis.
Augmented dermatology can lead to multiple advantages for dermatologists, such as:
Augmented dermatology is coming and will change the way dermatologists work today. Augmented dermatology will never replace dermatologists but instead help them function at a higher level. With artificial intelligence, dermatologists can reduce the risk of error, increase detection of malignant skin diseases, cope with a busy work schedule, and treat patients in a more holistic way for an optimal diagnosis.