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Objectives: Artificial intelligence (AI) is transforming aesthetic dermatology, introducing new opportunities for personalized, predictive, and adaptive approaches in skin diagnostics, treatment planning, and patient management. This review examines AI’s evolving role in enhancing diagnostic precision, individualizing treatments, and supporting dynamic patient care, with a focus on practical implementation in clinical settings. Results: This piece highlights how AI-based imaging and predictive tools enable more precise diagnostics and tailored treatment protocols, leading to improved patient outcomes and satisfaction. Some of the key benefits of AI in aesthetic dermatology include the ability to detect subtle skin changes, simulate treatment outcomes, and adjust interventions in real time. However, this manuscript also addresses significant challenges that practitioners face, such as technical constraints, data privacy concerns, algorithmic biases, and financial barriers, which impact the accessibility and efficacy of AI across diverse patient populations. Conclusions: While AI holds significant potential to enhance aesthetic dermatology, its responsible integration requires addressing these challenges through clinician training, ethical guidelines, and robust data security measures. Effective use of AI will depend on collaboration between technology developers, clinicians, and regulatory bodies. Perspectives: Looking forward, the development of diverse, inclusive datasets and transparent, patient-centered AI models will be essential to ensure that AI’s benefits reach all patients equitably and safely. By prioritizing these factors, AI-driven technologies would become a reliable, accessible, and transformative element of aesthetic dermatology practice.
Objectives: Artificial intelligence (AI) is transforming aesthetic dermatology, introducing new opportunities for personalized, predictive, and adaptive approaches in skin diagnostics, treatment planning, and patient management. This review examines AI’s evolving role in enhancing diagnostic precision, individualizing treatments, and supporting dynamic patient care, with a focus on practical implementation in clinical settings. Results: This piece highlights how AI-based imaging and predictive tools enable more precise diagnostics and tailored treatment protocols, leading to improved patient outcomes and satisfaction. Some of the key benefits of AI in aesthetic dermatology include the ability to detect subtle skin changes, simulate treatment outcomes, and adjust interventions in real time. However, this manuscript also addresses significant challenges that practitioners face, such as technical constraints, data privacy concerns, algorithmic biases, and financial barriers, which impact the accessibility and efficacy of AI across diverse patient populations. Conclusions: While AI holds significant potential to enhance aesthetic dermatology, its responsible integration requires addressing these challenges through clinician training, ethical guidelines, and robust data security measures. Effective use of AI will depend on collaboration between technology developers, clinicians, and regulatory bodies. Perspectives: Looking forward, the development of diverse, inclusive datasets and transparent, patient-centered AI models will be essential to ensure that AI’s benefits reach all patients equitably and safely. By prioritizing these factors, AI-driven technologies would become a reliable, accessible, and transformative element of aesthetic dermatology practice.
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