March 2026 in “Applied Sciences” AI in hair and scalp analysis shows promise but lacks real-world clinical integration and validation.
34 citations
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March 2009 in “Journal of Investigative Dermatology” Proteomic analysis can identify genetic differences in mouse hair, helping understand hair defects and variations.
1 citations
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September 2012 in “Revista Latinoamericana de Psicopatologia Fundamental” Gender identity doesn't determine who people are attracted to or their sexual practices.
July 2021 in “Advances in laboratory medicine” Diagnosing sex development disorders requires combining medical history, physical exams, imaging, lab tests, and genetic data.
1 citations
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September 2025 in “PLOS Digital Health” Large language models often give biased or inaccurate medical responses, especially for LGBTQIA+ prompts.
July 2025 in “Indian Journal of Forensic Medicine & Toxicology” DNA phenotyping can predict physical traits like eye, hair, and skin color, improving forensic investigations.
73 citations
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December 2015 in “Nature Genetics” Mutations in TBX3 cause horses to have more even hair color instead of Dun camouflage.
19 citations
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August 2022 in “Forensic Science International Genetics” The model accurately predicts age from saliva and buccal cells for forensic use.
1 citations
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August 2013 in “Journal of Clinical Epidemiology” The "exposure–crossover design" helps assess individual changes in risk after events like car crashes.
July 2022 in “Postepy biochemii” DNA markers can predict physical traits for forensic use, but there are ethical and technical challenges.
36 citations
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March 2019 in “European Journal of Human Genetics” The research found genetic differences in identical twins that could explain why one twin has a disease while the other does not.
April 2026 in “Therapeutic Advances in Drug Safety” Finasteride is high-risk for cognitive disorders, while Carbidopa/Levodopa, Topiramate, and Clonazepam are moderate-risk.
7 citations
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June 2015 in “EMBO Reports” Forensic DNA phenotyping can help generate new leads in cold cases but faces accuracy, legal, and acceptance challenges.
The model accurately diagnoses hair diseases with 95% accuracy using deep learning.
14 citations
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February 2018 in “Psychoneuroendocrinology” Mice lacking steroid 5α-reductase 2 show less aggression and better impulse control.
Better models and evaluation methods for alopecia areata are needed.
February 2024 in “JAAD International” Measuring the variety in hair thickness can help diagnose male pattern baldness in Korean men.
September 2024 in “Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi” XGBoost can effectively diagnose PCOS with 87% accuracy.
January 2026 in “Frontiers in Molecular Biosciences” A new method helps diagnose alopecia areata using specific gene markers and could guide targeted treatments.
May 2025 in “Psychoneuroendocrinology” Discrimination during pregnancy affects newborn stress hormone levels.
19 citations
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November 2021 in “Lupus Science & Medicine” Black patients with discoid lupus erythematosus have more severe skin damage and higher chances of dyspigmentation, scalp, and ear involvement.
August 2024 in “Clinical & experimental pathology” Forensic DNA phenotyping can now predict more physical traits and ancestry from DNA, but further improvements are needed.
2 citations
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May 2023 in “Biology” New mouse models of Pemphigus show severe symptoms and need better treatments.
85 citations
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June 2015 in “Scientific Reports” The study found that diseases can be grouped by symptoms and that the accuracy of predicting disease-related genes varies with the data source.
January 2009 in “The Chinese Journal of Modern Applied Pharmacy” The Potts-Guy model best predicts skin permeability for the tested drugs.
21 citations
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May 2023 in “The Journal of Allergy and Clinical Immunology In Practice” 8 citations
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August 2022 in “BMC Veterinary Research” C57BL/6 mice and SD rats have different sweat gland and hair follicle patterns, useful for skin research.
April 2012 in “The Journal of Urology” Male pattern baldness may predict prostate cancer risk.
Machine learning can accurately predict hair loss early, improving treatment options.
3 citations
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March 2024 in “arXiv (Cornell University)” The new AI system improves remote skin condition diagnosis and access to care.