2 citations
,
March 2023 in “Aesthetic Plastic Surgery” The new hair transplant method reduces scarring and wastage by combining two techniques.
13 citations
,
June 2014 in “Molecular therapy” The lentiviral array can monitor and predict gene activity during stem cell differentiation.
50 citations
,
March 2018 in “BMC Genomics” Non-coding RNAs help control hair growth cycles in cashmere goats, suggesting ways to improve cashmere production.
AI can predict hair loss patterns to improve care and treatment.
March 2026 in “Journal of Investigative Dermatology” Generative AI tools like GPT-4o can effectively automate SALT scoring for alopecia areata, matching clinician accuracy.
September 2023 in “Animals” Genes linked to wool fineness in sheep have been identified.
1 citations
,
June 2025 in “Frontiers in Genetics” Key genes IRF2BP2 and EGFR are linked to Hetian sheep's double-coat fleece.
7 citations
,
October 2023 in “BMC Genomics” Noncoding RNAs help determine cashmere quality in goats.
August 2001 in “Dermatologic Surgery” Elliptografting gives better hair appearance and satisfaction than other methods.
7 citations
,
August 2009 in “Applied Mathematics and Mechanics-English Edition” Hair fibers have fractal patterns with properties related to the golden mean, which may affect their functionality.
Transfer learning with three neural network architectures accurately classifies hair diseases.
February 1997 in “Dermatologic Surgery” Math skills are crucial for planning and executing successful hair restoration surgeries.
March 2026 in “Pediatric Dermatology” Generative AI tools can accurately score alopecia areata, reducing subjectivity in evaluations.
January 2021 in “Research Square (Research Square)” Long noncoding RNAs may help understand rabbit hair follicle density.
September 2020 in “Research Square (Research Square)” Long noncoding RNAs help regulate hair follicle density in rabbits.
October 2021 in “bioRxiv (Cold Spring Harbor Laboratory)” The Hair Cell Analysis Toolbox automates and improves the analysis of cochlear hair cells using machine learning.
24 citations
,
May 2022 in “BMC Veterinary Research” lncRNAs play a key role in hair follicle development, affecting cashmere quality and yield.
October 2007 in “Clinical Biochemistry” New genotype linked to non-classical congenital adrenal hyperplasia found in Italian siblings.
21 citations
,
October 2013 in “Molecular Biology of the Cell” The protein CCN2 controls hair growth by affecting hair follicle formation and stem cell activity in mice.
November 2024 in “Image Analysis & Stereology” The method improves hair image segmentation accuracy while reducing annotation costs.
42 citations
,
January 2017 in “Genes” The gene KAP22-1 affects wool yield and fiber shape in sheep.
10 citations
,
February 2019 in “Journal of Cellular Biochemistry” Specific RNA patterns are linked to alopecia areata.
7 citations
,
January 2015 in “Case reports in genetics” Using SNP array testing helped quickly find the gene causing Woodhouse-Sakati syndrome in two related individuals.
June 2024 in “Indian Journal of Plastic Surgery/Indian journal of plastic surgery” A new method helps ensure long-lasting hair transplant results by accurately calculating the donor area.
130 citations
,
January 2000 in “Nature biotechnology”
September 2025 in “Animals” Key proteins and pathways are crucial for wool fineness, but more research is needed.
October 2024 in “Zeitschrift für angewandte Mathematik und Physik”
November 2019 in “Hair transplant forum international” The SketchAndCalc app is a faster and more precise method for measuring hair transplant areas than traditional grid counting.
A new image-based method improves accuracy in measuring hair loss in mice.
December 2019 in “Periodicals of Engineering and Natural Sciences (International University of Sarajevo)” Machine learning can predict hair health accurately using personal data.