May 2026 in “International Journal of Technology in Education and Science” This study developed a leakage-resistant machine learning framework for classifying hair loss types, emphasizing transparency through explainable AI. Among tested models, Extreme Gradient Boosting excelled, achieving high accuracy and stability on both cross-validation and holdout datasets.
1 citations
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February 2024 in “npj digital medicine” This study developed a deep-learning model using unannotated dermatology images from online forums, achieving 49.64% accuracy in classifying 22 skin diseases and 61.76% accuracy in detecting monkeypox, highlighting the potential of these images for skin disease diagnostics in China.
1 citations
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December 2022 in “Journal of applied biological chemistry” This study found that TRP-hair essence significantly protected and improved the quality of human hair, particularly against heat stress, by enhancing cuticle health and maintaining hair color.
13 citations
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July 2024 in “Heart Failure Reviews” This review compiles data on how the apelinergic system may protect against heart damage caused by doxorubicin cancer treatment, suggesting its potential to mitigate cardiotoxicity, though further research in chronic models is needed to confirm these effects and mechanisms.
1 citations
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September 2016 in “Springer eBooks” This article reports no new data; it describes the role of sebum in influencing the skin microbiome and epithelial tissues and discusses its altered composition during transit through the sebaceous duct.