Artificial intelligence (AI) in dermatology is both promising and challenging. This is important for clinicians to recognize most up-to-date knowledge and advancements.
Advantages include timely detection and diagnosis, enhanced accuracy, efficient triage, workflow automation, personalized treatment, outcome prediction, education support, telemedicine aid, research facilitation, cost-efficiency, scalability, and drug development. However, limitations include generalizability issues, image quality variations, data requirements, interpretability concerns, patient acceptance, liability, multidisciplinary coordination challenges, data bias risks, lack of explainability, potential loss of clinical skills, security and privacy risks, resource intensiveness, integration challenges, validation and regulation gaps, and limited clinical assessment. Bridging these gaps requires robust ethical frameworks, interdisciplinary collaboration, education, regulation focusing on patient safety and privacy, standardized data sets, transparency, and human oversight.
Despite the challenges, AI holds significant potential to revolutionize dermatology practice, improving patient outcomes, healthcare accessibility, and research advancements. Further research and interdisciplinary collaboration are crucial to maximize AI's benefits and address its limitations effectively.