AI tools for AD show promise but lack real-world validation, scoping review shows

Stop Artificial intelligence (AI)-based tools could support the diagnosis, monitoring and management of atopic dermatitis (AD), but limited external validation, unrepresentative datasets, and a lack of testing within clinical pathways currently restrict their translation into practice, according to a recent scoping review. AI-driven tools are being developed to diagnose AD, assess disease severity, monitor symptoms and predict disease activity. But how ready these tools are for clinical use remains uncertain. As such, a scoping review published in the journal Clinical and Experimental Dermatology mapped the available research on AI-driven digital tools for AD, assessed study methodologies and identified barriers to their real-world implementation. The authors searched the MEDLINE, Embase, Web of Science and Scopus databases from their inception to December 2024. Eligible publications included primary research evaluating diagnostic aids, symptom-tracking applications, predictive models, AI-supported teledermatology systems and language-based tools.