September 2025 in “Psychoneuroendocrinology” Hair glucocorticoids link to type 2 diabetes but not to socioeconomic status.
January 2025 in “Nature Communications” Large-scale reconstructions enhance understanding of vibrissal sensory mapping in the brain.
December 2023 in “International Journal of Pharmaceutics” New nanoparticles deliver plant extracts to hair follicles to treat conditions like hair loss and acne.
August 2023 in “Micromachines” The new method can create hair follicle-like structures but not complete hair with roots and shafts, needing more improvement.
November 2020 in “bioRxiv (Cold Spring Harbor Laboratory)” Apoptotic cells may trigger cell death in hair follicles during their regression cycle.
April 2018 in “The journal of investigative dermatology/Journal of investigative dermatology” Double-stranded RNA helps regenerate hair follicles by increasing retinoic acid production and signaling.
January 2018 in “Refubium (Universitätsbibliothek der Freien Universität Berlin)” Nanocrystals and nanoparticles can enhance drug delivery for skin applications by improving solubility and dissolution rates.
September 2017 in “Journal of Investigative Dermatology” The new scalp treatment preserves hair color, reduces hair loss, and maintains hair strength.
January 2014 in “China Surfactant Detergent & Cosmetics” A reliable method was developed to measure finasteride in hair products.
248 citations
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September 2006 in “PLANT PHYSIOLOGY” Extracellular ATP is crucial for plant root growth and signaling.
Moisture makes hair flexible for reshaping during blowouts.
79 citations
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January 2015 in “Journal of Materials Chemistry B” Smart biomaterials that guide tissue repair are key for future medical treatments.
November 2025 in “Frontiers in Immunology” Stem cell activity influences autoimmune disease outcomes by affecting immune responses and tissue regeneration.
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.
November 2020 in “Journal of Pharmaceutical Sciences” The decision tree can predict drug absorption issues with good accuracy but needs more validation and adjustments for other factors.
September 2023 in “JP Journal of Biostatistics” The random forest model effectively helps diagnose COVID-19 using key factors like age and symptoms.
February 2023 in “International Journal of Multimedia Computing” The improved algorithm enhances low-dose CT image quality significantly better than other methods.
2 citations
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November 2024 Machine learning can accurately predict mental disorders.
1 citations
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February 2024 in “npj digital medicine” Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
5 citations
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July 2019 in “Applied statistics/Journal of the Royal Statistical Society. Series C, Applied statistics” Case-only trees and random forests improve predictions of treatment effects in clinical trials.
34 citations
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January 2020 in “IEEE Access” A model called PM-DBiGRU was developed for analyzing sentiments in drug reviews, and it performed better than other models, but struggled with complex sentences and situations requiring background knowledge.
1 citations
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September 2024 in “arXiv (Cornell University)” Reliable machine learning in medical imaging needs bias checks and data drift detection for consistent performance.
61 citations
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June 2022 in “IEEE Journal of Biomedical and Health Informatics” The new method improves skin cancer detection in imbalanced datasets.
April 2021 in “Journal of Investigative Dermatology” A deep learning model was developed to help diagnose trichothiodystrophy by analyzing hair patterns.
January 2021 in “arXiv (Cornell University)” Self-supervised learning improves medical image classification accuracy.
The model accurately classifies hair conditions with 97% accuracy.
AI can improve alopecia areata diagnosis with high accuracy.
The model accurately predicts hair loss severity in alopecia areata.
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.
Machine learning can accurately tell apart False Daisy and Smooth Joy Weed.