ReviewDermatology and therapy2026
Artificial Intelligence in Hair Disorders: A Narrative Review.
Review in Dermatology and therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is increasingly being incorporated into dermatology, with hair disorders representing a particularly suitable field for its application. The assessment and management of alopecias rely heavily on visual evaluation, pattern recognition, longitudinal monitoring, and integration of heterogeneous clinical and biological data; processes that are often limited by interobserver variability and incomplete standardization. In recent years, AI-based approaches have been applied across multiple domains in the clinical assessment of hair disorders, including objective quantitative assessment, diagnostic support, personalized medicine, drug development, robotic-assisted procedures, and analysis of patient-reported outcomes and clinical communication. Among these applications, tools enabling automated and reproducible measurement of hair parameters are currently the most established in clinical practice, whereas diagnostic and predictive models remain largely investigational. This narrative review summarizes current and emerging applications of artificial intelligence in hair disorders, with a focus on their clinical relevance and practical implementation. In addition, methodological limitations, ethical considerations, and challenges related to external validation, interpretability, and data bias are discussed. Although AI-based tools are not yet able to replace clinical judgement, they hold significant potential to complement dermatologists' expertise and improve objectivity, efficiency, and personalization in the management of hair disorders.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.