42 citations
,
January 2008 in “Dermatology” Dermoscopy effectively distinguishes between acute total hair loss and other types of female hair loss.
17 citations
,
September 2009 in “British Journal of Dermatology” Fragile hair in children is rarely linked to trichothiodystrophy (TTD).
iEdgePathDDA effectively finds new drug-disease links, outperforming other methods.
January 2026 in “Animals” TBX3 gene affects pigmentation and marking formation in Dun Mongolian horses.
April 2019 in “Journal of Investigative Dermatology” The search scheme SMRI is faster and more secure for retrieving encrypted data from the cloud.
July 2025 in “Journal of Investigative Dermatology” Machine learning can help identify biomarkers for personalized Pemphigus vulgaris treatment.
12 citations
,
January 1987 in “Carcinogenesis” TCDD changes skin cell growth and keratin production in mice.
September 2023 in “JEADV Clinical Practice” Dermoscopy helps diagnose folliculotropic mycosis fungoides by identifying specific skin patterns.
15 citations
,
November 2012 in “Archives of Ophthalmology” A deletion in the CDH3 gene causes a rare disorder with short hair and vision loss.
July 2021 in “Advances in laboratory medicine” Diagnosing sex development disorders requires combining medical history, physical exams, imaging, lab tests, and genetic data.
March 2024 in “European Journal of Neuroscience” Dopaminergic neurons in the gut have diverse subtypes with different neurotransmitter contents.
March 2024 in “bioRxiv (Cold Spring Harbor Laboratory)” Minoxidil treatment improves heart defects in a DiGeorge syndrome model.
15 citations
,
June 2021 in “Medicina” Combined light therapy improves eye health and quality of life for those with meibomian gland dysfunction.
June 2025 in “British Journal of Dermatology” The new AI software predicts melanoma outcomes more accurately than traditional methods.
5 citations
,
January 2024 in “Science Advances” Touch dome keratinocytes in adult skin have traits of different skin cell types.
January 2016 in “Huanjing yu Jiankang Zazhi” February 1996 in “Clinical Pharmacology & Therapeutics” MK-386 reduces sebum DHT levels.
1 citations
,
October 2022 in “International Journal of Environmental Research and Public Health” People with Type 2 Diabetes are more likely to have a mite infestation called Demodex folliculorum.
5 citations
,
July 2019 in “Photodiagnosis and photodynamic therapy” Using tacalcitol ointment with photodynamic therapy may effectively treat follicular mucinosis with scalp hair loss.
48 citations
,
June 2000 in “Japanese Journal of Cancer Research” Dimethylarsinic acid speeds up skin tumor growth in certain mice.
January 2025 in “Communications in computer and information science” HairLossMultinet accurately classifies hair damage with 98% accuracy but needs a more diverse dataset for broader use.
January 2015 in “Indian Journal of Dermatology, Venereology and Leprology” The document concludes that various skin conditions have specific characteristics and treatments, and highlights the importance of vitamin D in managing these dermatological issues.
2 citations
,
January 2022 in “Actas Dermo-Sifiliográficas” Dermoscopy can effectively identify Malassezia folliculitis.
July 2024 in “Journal of Investigative Dermatology” A KLK5 inhibitor effectively improved skin symptoms in a mouse model of Netherton Syndrome.
A patient with Myotonic dystrophy type 1 had multiple tongue hemangiomas and was sensitive to anesthesia.
1 citations
,
January 2018 in “Indian dermatology online journal” The girl has both monilethrix and Type 1 diabetes, but no link between the two conditions is known.
13 citations
,
November 2007 in “Journal of Structural Biology” Keratin heterodimers are preferred for their specific and structural advantages.
3 citations
,
October 2023 in “Journal of Pain” Certain proteins might predict surgical success in trigeminal neuralgia treatment.
5 citations
,
June 2023 in “Engineering Technology & Applied Science Research” The AI model accurately classifies Alopecia Areata with 96.94% accuracy.
January 2021 in “arXiv (Cornell University)” Self-supervised learning improves medical image classification accuracy.