79 citations
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July 2022 in “Sensors” Machine learning can effectively predict type 2 diabetes risk.
8 citations
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August 2021 in “Computational and Mathematical Methods in Medicine” Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.
5 citations
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March 2022 in “Clinical Cosmetic and Investigational Dermatology” The study developed a facial phenotype prediction model that accurately predicted skin conditions in Korean women by analyzing genotype information and employing machine-learning methods. This model demonstrated potential utility in the development of customized cosmetics, offering an optimal solution for tailoring skincare products to individual genetic profiles.
3 citations
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January 2025 in “BMC Medical Informatics and Decision Making” Machine learning can help find new ways to treat alopecia areata.
3 citations
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October 2022 in “Nano Letters” Machine learning identified promising nanozymes for treating hair loss.