Affiliation:
1. Department of Dermatology Mazandaran University of Medical Sciences Sari Iran
2. Department of Medical Sciences Stanford University Stanford CA USA
3. Department of Dermatology Apollo Clinic Silchar Silchar Assam India
4. Department of Dermatology Venereology and Leprosy, Dhubri Medical College and Hospital Dhubri Assam India
Abstract
AbstractBackgroundThe integration of artificial intelligence (AI) in dermatology is revolutionizing the diagnostic methods and management strategies and hence is uplifting the overall patient care. AI technologies have shown a significant potential in automated diagnosis, severity assessment of chronic cutaneous diseases like psoriasis, and the development of comprehensive dermatological databases is helping in swift disease detection.ObjectiveThis review aims to explore the current landscape and future potential of AI in inflammatory skin diseases. It focuses on various automated diagnostic systems, the role of AI in assessment and staging of chronic inflammatory dermatological conditions, and the importance of dermatological databases. The review also addresses the various challenges associated with AI implementation.MethodsA extensive literature search was conducted from databases namely, PubMed, Google Scholar, and Embase. Search terms included combinations of “artificial intelligence,” “deep learning,” “dermatology,” “automated diagnosis,” and “dermatological databases” from different field of study. Articles were selected and reviewed based on relevance and quality, highlighting studies demonstrating AI's impact on diagnosis and management.ResultsAI‐powered diagnostic systems have ominously advanced, offering noninvasive and accessible diagnostic tool(s) that use extensive datasets to improve accuracy and efficacy across different populations. The development of dermatological databases is fundamental for training of different AI models. Despite these advances, challenges related to data privacy, regulatory oversight, and inclusivity in AI models persist. Addressing these challenges is essential for augmenting and optimizing AI's potential in dermatology.ConclusionAI is set to transmute dermatology by augmenting diagnostic precision, customizing treatment plans, and making dermatological care more reachable, particularly in underprivileged areas. This review highlights the various advances made in AI for the diagnosis and management of inflammatory skin disorders, acknowledging the ethical and technical hurdles that need to be addressed.