A machine-learning test using hair can help detect autism early in infants.
822 citations
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January 2021 in “Genome biology” scMC effectively separates biological signals from technical noise in single-cell genomics data.
November 2023 in “Computational and Structural Biotechnology Journal” A single robotic system can accurately harvest and implant hair grafts, showing promise for real-world use.
April 2026 in “Scientific Reports” The tool accurately tracks eyebrow hair loss in chemotherapy patients.
March 2026 in “FMDB Transactions on Sustainable Health Science Letters” A deep learning method can detect nutritional deficiencies from hair and nail images with 89% accuracy.
46 citations
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December 2018 in “Biomedical Optics Express” Raman spectroscopy could effectively guide skin cancer surgery by identifying tumor margins.
August 2024 in “Clinical Case Reports” Pilomatricoma is a rare, benign skin tumor that requires surgical removal for best results.
39 citations
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January 2020 in “Scientific Reports” Four circRNAs were found to be significantly different in cashmere goat skin, affecting cashmere fineness.
19 citations
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October 2024 in “BMC Medical Informatics and Decision Making” AI can improve early diagnosis and classification of PCOS, aiding in prevention of related health issues.
November 2023 in “Research Square (Research Square)” NIR-II imaging effectively tracked stem cells that helped repair facial nerve defects in rats.
Machine learning can accurately tell apart False Daisy and Smooth Joy Weed.
January 2026 in “JDDG Journal der Deutschen Dermatologischen Gesellschaft” Deep-learning models can effectively diagnose and assess Alopecia areata using scalp images.
7 citations
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October 2023 in “Indian Journal of Plastic Surgery” Robotics in facial injections offers precision but is costly and lacks personal touch.
February 2024 in “arXiv (Cornell University)” Adjusting AI training data for skin condition distribution improves accuracy across different clinical settings.
25 citations
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December 2008 in “Journal of Dermatological Case Reports” In vivo reflectance confocal microscopy is useful for evaluating hair shaft diseases but needs improvement for deeper hair follicle issues.
AI models are effective for detecting alopecia areata but face challenges like explaining results and data bias.
8 citations
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August 2021 in “Computational and Mathematical Methods in Medicine” Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.
1 citations
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October 2024 in “Dermatology Practical & Conceptual” Reflectance confocal microscopy is a promising non-invasive tool for diagnosing alopecia areata incognita.
February 2022 in “arXiv (Cornell University)” A new method accurately captures and renders hair color for real and synthetic images.
17 citations
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September 2022 in “Biomaterials Research” The film-trigger applicator improves microneedle skin delivery and drug efficiency using simple finger force.
109 citations
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April 1997 in “Archives of Dermatological Research” Mast cell and nerve fiber interactions in mouse skin change with the hair cycle.
The model accurately classifies hair conditions with 97% accuracy.
6 citations
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September 2025 in “Scientific Reports” Machine learning can accurately diagnose PCOS non-invasively using clinical and ultrasound features.
21 citations
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September 2008 in “Magnetic Resonance Imaging” MRI can effectively image skin structures noninvasively.
1 citations
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August 2022 in “Pigment Cell & Melanoma Research” New mouse models help study melanocytic cells for melanoma research.
October 2015 in “CRC Press eBooks” Follicular transplantation is effective for treating hair loss and eyebrow alopecia.
February 1985 in “PubMed” May 2026 in “International Journal of Technology in Education and Science” The AI system accurately classifies hair loss types and explains its decisions.
6 citations
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August 2016 in “Journal of Visualized Experiments” The CUBIC protocol allows detailed 3D visualization of proteins in mouse skin biopsies.
3 citations
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February 2024 in “arXiv (Cornell University)” Google Search ads effectively gathered a diverse dermatology image dataset for research and AI development.