Trichoscopy and Computational Models for Hair and Scalp Disorders: Image Analysis, Quantification, and Clinical Integration

    March 2026 in “ Applied Sciences ”
    Corrado Zengarini, Nico Curti, Stephano Cedirian, Luca Rapparini, Francesca Pampaloni, Alessandro Pileri, Francesco Durazzi, Martina Mussi, Michelangelo La Placa, Bianca Maria Piraccini, Michela Starace
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    Studysummary In this scoping review, researchers observed that while AI-assisted trichoscopy holds promise for standardized assessments of hair and scalp disorders, its clinical translation is limited by small proprietary datasets, inconsistent validation protocols, and a scarcity of real-world clinical studies. Our plain-language summary of this paper — not a Tressless recommendation.
    The document reviews the integration of AI and computational models in trichoscopy for diagnosing hair and scalp disorders, emphasizing the transition from manual to automated systems that improve accuracy and reproducibility. AI models, particularly deep learning, have shown high accuracy in diagnosing conditions like alopecia, with some achieving up to 98% accuracy. Despite these advancements, challenges such as limited datasets, proprietary data, and lack of standardized protocols hinder clinical translation and real-world application. The review underscores the potential of AI to standardize diagnostics in trichology and highlights the need for future research to focus on standardized imaging, transparent data reporting, and shared benchmarking frameworks to enhance clinical integration and validation.
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