Advancements in Artificial Intelligence for Dermatology and Healthcare

Abstract

Healthcare is revolutionizing through Artificial Intelligence (AI) integration in dermatology, leading to better diagnostic precision for patients and improved individualized treatments and healthcare results. This paper reviews how AI technologies advance dermatological diagnostic practices, especially for early skin cancer identification and classification, together with disease management processes.

Methods: The review of research integrates studies about AI implementation for dermatology through deep learning algorithms from sources including PubMed and, IEEE Xplore and Scopus from 2018 to 2024. The research evaluates the effects of AI on diagnostic technologies for imaging while examining the use of AI in therapeutic interventions along with its predictive capabilities concerning skin health.

Results: Multiple AI technologies working harmoniously have improved dermatological diagnosis through complex image analytic methods that generate superior results for skin cancer detection compared to standard procedures. Machine learning models perform superior diagnostic capabilities than dermatologists in various diagnostic situations. AI decision support technology enhances resource distribution, patient care routes, and personal treatment plans to produce better healthcare results.

Conclusion: The implementation of AI technologies in dermatology requires a solution to data quality issues and improvements in algorithm transparency together with ethical solutions for privacy and bias challenges. Future investigations must tackle current obstacles on their way toward achieving optimum implementation of AI systems in clinical practice.