March 2026 in “Mendeley Data” rwSALT provides precise hair regrowth measurement from scalp photos.
August 2001 in “Dermatologic Surgery” Elliptografting gives better hair appearance and satisfaction than other methods.
4 citations
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August 2024 in “Non-coding RNA Research”
March 2026 in “Mendeley Data” rwSALT accurately measures hair regrowth in alopecia areata using scalp photos.
November 2024 in “Image Analysis & Stereology” The method improves hair image segmentation accuracy while reducing annotation costs.
3 citations
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January 2019 in “Electronic Imaging” The device accurately estimates natural hair color at the roots in real time.
The KRT84 gene is linked to better wool quality in Gansu Alpine Fine-wool sheep.
39 citations
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September 2018 in “American Journal of Medical Genetics Part A” A new genetic mutation in the ODC1 gene causes developmental delay and other symptoms in a young girl.
July 2024 in “Journal of Investigative Dermatology” Machine learning can use blood tests to help predict moderate-to-severe alopecia areata.
12 citations
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January 2023 in “AAPS PharmSciTech” 1 citations
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September 2020 in “Journal of dermatology” Researchers found a new mutation in the LIPH gene of a woman with a rare hair condition.
2 citations
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December 2018 in “International Journal of Dermatology” New grading scale accurately measures hair loss severity and treatment effectiveness.
October 2025 in “Frontiers in Artificial Intelligence” "HairSentinel" accurately detects hairfall trends using simple user data, helping identify health risks early.
17 citations
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June 2020 in “Animals” lncRNAs may regulate hair follicle development in Hu sheep.
9 citations
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January 2020 in “IEEE Access” The KEBOT system is a highly accurate AI tool for analyzing hair transplants.
May 2024 in “JCI insight” A variant in the ADAM17 gene causes hair loss by increasing protein degradation through TRIM47.
129 citations
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October 2017 in “BMC Genomics” The study improved understanding of gene roles in cashmere goat hair growth, aiding future cashmere production.
September 2024 in “PubMed” Certain RNAs may help diagnose alopecia areata by affecting keratin genes.
The model accurately diagnoses hair diseases with 95% accuracy using deep learning.
37 citations
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May 2018 in “Frontiers in physiology” Certain RNA molecules are important for the development of wool follicles in sheep.
Machine learning can accurately predict Polycystic Ovary Syndrome in women using clinical features.
4 citations
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September 2019 in “Biomedical Papers/Biomedical Papers of the Faculty of Medicine of Palacký University, Olomouc Czech Republic” CD2 might be a new treatment target for patchy alopecia areata.
December 2019 in “Periodicals of Engineering and Natural Sciences (International University of Sarajevo)” Machine learning can predict hair health accurately using personal data.
1 citations
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March 2015 in “Journal of Visualized Experiments” Researchers developed a new, precise method to measure hair loss in mice using image analysis.
July 2024 in “Journal of Investigative Dermatology” Modulating the BTNL2 pathway can prevent hair loss in mice.
March 2025 in “Journal of Craniofacial Surgery” Natural hairline asymmetry should be embraced for better-looking hair transplants.
3 citations
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August 2020 in “bioRxiv (Cold Spring Harbor Laboratory)” The DNN-DTIs method accurately predicts drug-target interactions and is useful for drug repositioning.
7 citations
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March 2018 in “Asian-Australasian journal of animal sciences” OCIAD2 and DCN genes affect hair growth in goats by having opposite effects on a growth signaling pathway and inhibiting each other.
9 citations
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March 2014 in “Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE” The new image descriptor helps identify skin cancer structures with good accuracy.
5 citations
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January 2025 in “BMC Medical Informatics and Decision Making” Computer vision techniques can help detect and assess skin conditions like vitiligo, alopecia areata, and dermatitis.