Comprehensive Summary
Thunga et al write a review exploring the current and future integration of AI in diagnostic and aesthetic dermatology, while contrasting it with AI uses in diagnosing skin conditions. Additionally, the authors review proposed solutions to address the existing limitations. AI applications from both diagnostic and aesthetic dermatology fields were analyzed through their traditional survey methods like subjective surveys and hardware devices. The review concluded that there is a lot of potential for AI to diagnose skin disease, especially skin cancer. However, in aesthetic dermatology, current methods have limited effectiveness because they are subjective and not standardized. Additionally, the emerging AI technologies are promising, but they are limited by biased datasets and inconsistent evaluation methods.
Outcomes and Implications
New technologies have been beneficial in diagnosing skin disease, but aesthetic dermatology, in particular, faces unique challenges that have yet to be addressed by AI, including current subjective evaluation methods. To develop the potential of AI in aesthetic dermatology, it is important to collect datasets that represent various ethnicities and ages, and use these datasets to create standardized evaluation methods. Once these challenges are addressed, AI will have a higher diagnostic accuracy, better patient outcomes, which will allow it to be integrated more effectively into clinical practice.