8 citations
,
January 2019 in “Turkish journal of medical sciences” Ischemic modified albumin could be a new indicator of oxidative stress in people with alopecia areata.
7 citations
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March 2024 in “Scientific Reports” The neighborhood face index (NFI) accurately predicts properties of complex molecules.
7 citations
,
September 2014 in “Journal of Obstetrics and Gynaecology Research” Ultrasound measurement of the ovarian stroma to total area ratio is not a reliable single predictor of high male hormone levels in Thai women with PCOS, but works better when combined with clinical signs.
6 citations
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January 2024 in “Journal of Cancer” A gene-based model predicts lung adenocarcinoma outcomes and helps guide treatment decisions.
5 citations
,
May 2020 in “Diagnostics” Lower zinc levels may predict less effective hair loss treatment.
2 citations
,
November 2024 Machine learning can accurately predict mental disorders.
2 citations
,
November 2024 in “International Journal of Pharmaceutics X” Desmopressin-loaded liposomes can effectively deliver drugs through the skin, improving bioavailability and patient compliance.
2 citations
,
September 2024 in “Skin Research and Technology”
1 citations
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November 2023 in “BMC chemistry” Tadalafil and Finasteride may help treat aggressive melanoma.
1 citations
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November 2023 in “Research Square (Research Square)” DiZyme accurately predicts nanozyme activities to aid in discovering new applications.
August 2025 in “International Journal of Molecular Sciences” AVT is highly conserved and may have antimicrobial properties.
July 2025 in “Archives of Toxicology” The new skin model can predict how chemicals might cause skin allergies.
July 2025 in “Indian Journal of Forensic Medicine & Toxicology” DNA phenotyping can predict physical traits like eye, hair, and skin color, improving forensic investigations.
December 2024 in “International Journal of experimental research and review” Adding obesity data to machine learning models improves heart disease prediction accuracy.
November 2023 in “Biology” N6-methyladenosine affects hair follicle development differently in Rex and Hycole rabbits.
Cialis and Finasteride could be repurposed to treat aggressive melanoma.
December 2021 in “Acta dermato-venereologica” A deep learning model accurately predicts male hair loss types using scalp images.
November 2021 in “International Journal of Trichology” Low PON1 levels may indicate and predict the severity of hair loss.
10 citations
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January 2019 in “Biomarker Insights” Scalp cooling to prevent hair loss from chemotherapy works for some but not all, and studying hair damage markers could improve prevention and treatment.
7 citations
,
June 2019 in “Coloration Technology” Translucent keratin films are better for testing hair dyes.
2 citations
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January 2019 in “Dermatology Review” Pigmented vellus and upright regrowing hairs predict hair regrowth in severe alopecia.
July 2025 in “Discover Mental Health” Loneliness reduces academic enthusiasm in students.
January 2025 in “International Journal of Trichology” Severe hair loss may increase the risk of dying from COVID-19.
October 2023 in “Dermatology practical & conceptual” Finger length ratios might help predict common hair loss.
2 citations
,
June 2017 in “Journal of The American Academy of Dermatology” The type of PCOS a woman has doesn't strongly predict her skin or metabolic symptoms; obesity is a more important factor.
1 citations
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December 2012 in “Journal of the European Academy of Dermatology and Venereology” The health of the sentinel lymph node is the best indicator of survival for patients with thick skin cancer.
July 2025 in “Journal of Investigative Dermatology” Machine learning can help identify biomarkers for personalized Pemphigus vulgaris treatment.
October 2023 in “Skin health and disease” Alopecia areata costs individuals about 3% of their income, with women, Asians, those with lower income, and more severe symptoms spending more.
October 2017 in “European Neuropsychopharmacology” 5 citations
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March 2022 in “Clinical Cosmetic and Investigational Dermatology” The model accurately predicts skin conditions in Korean women using genetic information, aiding personalized skincare.