2 citations
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August 2020 in “Cosmetics” Herbal formula shows promise for hair loss treatment.
September 2024 in “Journal of the American Academy of Dermatology” December 2021 in “Acta dermato-venereologica” A deep learning model accurately predicts male hair loss types using scalp images.
January 2025 in “Kuwait Journal of Science” KRT71 gene variants may influence camel hair shape but don't fully explain it.
March 2026 in “Frontiers in Medicine” A hybrid model using traditional methods, trichoscopy, and AI improves hair loss assessment.
9 citations
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June 2012 in “Joint Conference on Lexical and Computational Semantics” The gel effectively thickens eyelashes and eyebrows without side effects.
6 citations
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February 2025 in “Scientific Reports” MEGA PROTAC improves prediction and ranking of protein complexes better than existing methods.
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December 2017 in “Small Ruminant Research” Variation in the TCHH gene affects wool curliness in sheep.
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December 2018 in “Methods in molecular biology” The document concludes that computational methods using networks and various data can improve the process of finding new uses for existing drugs.
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December 2021 in “Electronics” The new method predicts post-hair transplant images more accurately than other methods.
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May 2024 in “Skin Appendage Disorders” Early diagnosis with trichoscopy can improve management and quality of life for CCCA patients.
16 citations
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April 2017 in “ACM Transactions on Graphics” Light scatters differently from elliptical hair fibers than from circular ones, and a new model better predicts this behavior, especially for shiny highlights.
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June 2022 in “Jambura Journal of Mathematics” The Vogel Total Difference Approach Method helps reduce shipping costs in production delivery.
March 2026 in “International Journal of Science Strategic Management and Technology” WomenCare helps predict PCOD risk in women to encourage early medical consultation.
February 1997 in “Dermatologic Surgery” Math skills are crucial for planning and executing successful hair restoration surgeries.
16 citations
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May 2023 in “Journal of the American Statistical Association” A new method makes analyzing large datasets with rare events faster and more efficient.
February 2024 in “arXiv (Cornell University)” Adjusting AI training data for skin condition distribution improves accuracy across different clinical settings.
September 2025 in “International Society of Hair Restoration Surgery” Printable templates improve hair transplant accuracy and efficiency.
Deep learning can improve non-invasive alopecia diagnosis using hair images.
December 2019 in “Journal of Cosmetic Dermatology” A new training model using an orange helps surgeons practice parietal whorl hair transplants effectively.
3 citations
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April 2022 in “Cutis” CCCA is a common, scarring hair loss in Black women that needs early detection.
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June 2021 in “Scientific Reports” Hair fiber shape and curvature are not significantly linked when ancestry is considered.
April 2026 in “Therapeutic Advances in Drug Safety” Finasteride is high-risk for cognitive disorders, while Carbidopa/Levodopa, Topiramate, and Clonazepam are moderate-risk.
January 2026 in “Dermatology Online Journal” CCCA can appear as patchy hair loss in younger men, not just the usual pattern.
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July 2020 in “JAMA dermatology” Dermatoscopy can help diagnose CCCA without visible hair loss, offering a less invasive option than biopsy.
July 2024 in “Journal of Education For Sustainable Innovation” Visualizing data helps guide future androgenetic alopecia research and policies.
June 2024 in “World Journal of Management Science” Data visualization tools are crucial for understanding and advancing androgenetic alopecia research.
April 2024 in “Archives of Dermatological Research” The approach improves scalp surgery results by tailoring techniques to defect size and location.
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December 2020 in “PLOS Genetics” New method finds genetic links between Type 2 Diabetes and Prostate Cancer not seen before.
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January 2011 in “Frontiers in Systems Neuroscience” Choosing the right model order in brain connectivity analysis can affect the detection of differences between healthy individuals and those with seasonal affective disorder.