9 citations
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January 2011 in “Skin Research and Technology” This study developed a high-resolution phototrichogram system that can automatically and accurately assess hair growth metrics in cosmetic trials, achieving over 90% correlation with manual measurements.
February 2026 in “Dermatology and Therapy” 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.
January 2018 in “International Journal of Advances in Scientific Research and Engineering” This study presents a new automated method for measuring total phenolic compounds in Ziziphus Jujuba fruit extract, showing high precision and potential applications in health and environmental sciences.
38 citations
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May 2009 in “European journal of dermatology/EJD. European journal of dermatology” This study found that the TrichoScan method for evaluating hair loss showed excellent correlation with manual marking and provided more consistent, reproducible results with less variability and operator error.
20 citations
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December 2017 in “Journal of Investigative Dermatology Symposium Proceedings” This article presents a computer imaging algorithm that may automate and enhance the Severity of Alopecia Tool scoring for alopecia areata through texture analysis of pediatric images.