3 citations
,
January 2018 in “International Journal of Trichology” The new system helps detect and track early female hair loss better.
August 2023 in “The Kitakanto Medical Journal” Image analysis can effectively identify changes in scalps affected by chemotherapy-induced hair loss.
April 2025 in “Journal of Cosmetic Dermatology” The AI device accurately grades scalp exfoliation and can help diagnose scalp disorders.
1 citations
,
March 2024 in “Skin research and technology” A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.
3 citations
,
January 2025 in “动物学研究” The gene GJA1 is important for regulating coarse hair density in goats.
10 citations
,
November 2018 in “bioRxiv (Cold Spring Harbor Laboratory)” New laser particles can track thousands of cells in 3D models, improving single-cell analysis.
November 2009 in “Hair transplant forum international” Dr. Bernard Cohen created a new system to classify hair loss using numbers and a detailed scalp map.
January 2026 in “AppliedMath” Pattern mode isolation improves the reliability and predictability of Turing patterns.
January 2025 in “EXPERIMENTAL ANIMALS” Gamma-ray exposure improves genome editing efficiency in mice using the i-GONAD method.
5 citations
,
October 2023 in “International Journal on Recent and Innovation Trends in Computing and Communication” The method accurately detects and classifies scalp diseases, including alopecia areata, with 89.3% accuracy.
2 citations
,
January 2024 in “IEEE Access” AlopeciaDet accurately detects Alopecia Areata early using advanced image analysis.
January 2009 in “Yaowu fenxi zazhi” The method accurately and reliably detects residual solvents in Finasteride.
11 citations
,
May 2011 in “The Journal of Dermatology” A man had two rare autoimmune diseases that might be connected.
May 2024 in “International journal of medicine and psychology.” Ganser syndrome may result from both organic and psychogenic factors.
The model explains how mammal ear hair cells respond to sound and adapt.
22 citations
,
May 2002 in “Skin Research and Technology” CE-PTG detects early hair follicle issues in balding areas, helping measure male hair loss.
March 2026 in “Pediatric Dermatology” Generative AI tools can accurately score alopecia areata, reducing subjectivity in evaluations.
51 citations
,
May 2004 in “American journal of ophthalmology” Using topical prostaglandin F2α for glaucoma may cause loss of eyelash or eyebrow pigment.
March 2026 in “Zenodo (CERN European Organization for Nuclear Research)” The N-K GM Series offers a free, effective solution to eliminate aflatoxin and cancer, improving health and life expectancy.
Combining FUT and FUE techniques improves hair transplant results for severe baldness in Asians.
November 2022 in “bioRxiv (Cold Spring Harbor Laboratory)” Using deep learning to predict gene expression from images could help assess colorectal cancer metastasis.
2 citations
,
January 2024 in “Journal of Emerging Investigators” A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.
1 citations
,
December 2022 in “BMC Genomics” The Msx2 gene affects feather development in Hungarian white geese and a specific gene variation could indicate feather quality.
November 2025 in “Scientific Reports” AI improves accuracy and consistency in diagnosing male pattern hair loss.
3 citations
,
October 2021 in “bioRxiv (Cold Spring Harbor Laboratory)” scINSIGHT helps understand single-cell gene expression better than current methods.
July 2025 in “Journal of the American Academy of Dermatology” Hair diameter diversity helps assess hair loss, but its standard measure varies by individual and ethnicity.
3 citations
,
July 2015 in “oURspace (University of Regina)” The method effectively grouped tweets into categories without knowing the number of groups beforehand.
April 2023 in “Journal of Investigative Dermatology” A new image-based method improves accuracy in measuring hair loss in mice.
June 2024 in “Nature Cell and Science” The Scalp Coverage Scoring method reliably measures hair density from images.
Deep learning can improve non-invasive alopecia diagnosis using hair images.