October 2022 in “Hair Transplantation” Reconstructing temporal points in hair restoration is crucial for a natural look.
December 2022 in “IntechOpen eBooks” Forensic DNA Phenotyping accurately predicts physical traits and is used in investigations, but needs more diverse population data for confirmation.
2 citations
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January 2024 AI can predict hair loss by analyzing genetic, scalp, and lifestyle data.
Machine learning can accurately predict hair loss early, improving treatment options.
July 2024 in “Journal of Investigative Dermatology” April 2021 in “Journal of Investigative Dermatology” A deep learning model was developed to help diagnose trichothiodystrophy by analyzing hair patterns.
Nonlinear artificial neural networks are better at identifying different types of animal hair than linear ones.
July 2025 in “Indian Journal of Forensic Medicine & Toxicology” DNA phenotyping can predict physical traits like eye, hair, and skin color, improving forensic investigations.
May 2026 in “International Journal of Technology in Education and Science” The AI system accurately classifies hair loss types and explains its decisions.
December 2019 in “Periodicals of Engineering and Natural Sciences (International University of Sarajevo)” Machine learning can predict hair health accurately using personal data.
4 citations
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November 2023 in “ArXiv.org” A new method improves the accuracy and reliability of language models by up to 42%.
December 2019 in “Periodicals of Engineering and Natural Sciences (PEN)” Hair analysis can provide insights into a person's medical history and location over time.
April 2026 in “Scientific Reports” The tool accurately tracks eyebrow hair loss in chemotherapy patients.
8 citations
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May 2025 in “Biomolecules” Forensic genetics can now predict physical traits and lifestyle habits, with future advancements expected from new technologies.
July 2026 in “International Journal of Advanced Research in Science Communication and Technology” BaldGraphFormer accurately predicts early baldness, aiding better hair loss treatment.
June 2023 in “International journal on recent and innovation trends in computing and communication” Combining multiple algorithms predicts hair fall more accurately than using single algorithms.
1 citations
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May 2016 in “Dermatologic Surgery” The document concludes that using a phototrichogram with a protractor and tapeline is a reliable and noninvasive way to measure hair loss.
44 citations
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June 2023 in “Cell Reports” IL-1 promotes fat cell growth in skin, while WNT inhibits it and encourages scar formation.
5 citations
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November 2023 in “Journal of Investigative Dermatology” Microthermal wounds heal with less scarring due to delayed collagen production and minimal inflammation.
3 citations
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September 2024 3DEEP reveals early hair follicle stem cell formation and niche establishment before hair bulb development.
3 citations
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November 2021 in “Frontiers in Genetics” Certain genes are linked to the quality of cashmere in goats.
December 2023 in “Journal of Investigative Dermatology” A specific type of immune cell plays a key role in causing alopecia areata and could be a target for treatment.
April 2023 in “The journal of investigative dermatology/Journal of investigative dermatology” Researchers found three types of melanocytes in developing mouse skin, each with different genes and locations.
June 2013 in “Annals of the Rheumatic Diseases” Specialist nurses play a crucial role in managing lupus and empowering patients.
The model accurately predicts hair loss severity in alopecia areata.
April 2026 in “International Journal of Engineering Research and Science & Technology” The new AI system accurately diagnoses hair disorders and offers personalized treatment recommendations.
4 citations
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March 2024 in “Forensic Sciences Research” Forensic DNA phenotyping faces challenges like inconsistent terms and limited genetic knowledge.
2 citations
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January 2024 in “Journal of Emerging Investigators” A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.
5 citations
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January 2009 in “Elsevier eBooks” Bayesian networks are tools for modeling variables' probabilistic relationships, which can efficiently represent complex probabilities and help in making inferences.
4 citations
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August 2020 in “bioRxiv (Cold Spring Harbor Laboratory)” The tool iCOUNT helps understand how stem cells divide and affect tissue development and repair.