From Diagnosis To Prognosis: A Scoping Review Of Artificial Intelligence In Alopecia Research

This review found that AI in dermatology shows high diagnostic accuracy comparable to experienced clinicians, but integration into clinical practice faces challenges requiring further research.

This review highlights current and future AI applications in hair restoration and diagnosis of hair disorders, including automated systems for hair detection and self-diagnosis, emphasizing the need for experts to understand their benefits and limitations.

This narrative review found that while AI-based tools in dermatology, particularly for hair disorder assessment, have potential to enhance clinical practice by improving objectivity and personalization, they currently serve mainly a complementary role and face challenges like methodological limitations and data bias.

In this study, researchers aim to use AI-related methods to predict different hair loss patterns, including male and female pattern baldness, alopecia areata, telogen effluvium, and traction alopecia, though specific results are not reported.