1 citations
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August 2023 in “arXiv (Cornell University)” Deep learning effectively diagnoses scalp disorders, but improvements are needed.
Nonlinear artificial neural networks are better at identifying different types of animal hair than linear ones.
A hat with sensors can measure scalp moisture well, helping with hair care.
June 2025 in “British Journal of Dermatology” The new AI software predicts melanoma outcomes more accurately than traditional methods.
April 2026 in “Laboratory Animal Research” The new Hairless R/J mice model improves imaging for tumor monitoring and cancer therapy evaluation.
July 2025 in “PNAS Nexus” A new tool accurately identifies human cornea cell states and key factors.
18 citations
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January 2020 in “Frontiers in Chemistry” A new model can predict drug-disease links well, helping drug research.
2 citations
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November 2024 Machine learning can accurately predict mental disorders.
15 citations
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August 2020 in “Indonesian Journal of Electrical Engineering and Computer Science” The system can automatically classify scalp conditions with 85% accuracy.
September 2022 in “Research Square (Research Square)” The AI model DIET-AI effectively diagnoses skin diseases as well as doctors.
The digital system for measuring melasma shows promise but needs more development for better accuracy and automation.
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.
25 citations
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November 2010 in “Journal of Molecular Structure” Raman micro-spectroscopy can help distinguish basal cell carcinoma from hair follicles in skin tissue.
November 2023 in “Research Square (Research Square)” NIR-II imaging effectively tracked stem cells that helped repair facial nerve defects in rats.
2 citations
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March 2025 in “PNAS Nexus” Raman spectroscopy can detect radiation exposure in mouse hair with high accuracy for up to 7 days.
2 citations
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February 2018 Raman spectroscopy can help identify cancerous skin tissue during surgery.
3 citations
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July 2023 in “Nature Communications” The ShorT method can detect and help reduce bias in medical AI by identifying shortcut learning.
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.
April 2026 in “Scientific Reports” The tool accurately tracks eyebrow hair loss in chemotherapy patients.
1 citations
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December 2014 in “Scanning” Multiphoton microscopy effectively images rabbit skin structures in detail without staining and shows differences from human skin.
The optimized VGG19 model accurately classifies hair diseases with 98.64% accuracy.
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.
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 1985 in “PubMed”
1 citations
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December 2022 in “JAMA Dermatology” The AI system HairComb accurately scores hair loss severity, matching dermatologist assessments.
20 citations
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April 2011 in “British Journal of Dermatology” Reflectance confocal microscopy can tell apart white dots on the scalp as either sweat gland ducts or hair follicle openings.
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.
5 citations
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July 2023 in “Journal of Autonomous Intelligence” Artificial neural networks can accurately diagnose Alopecia Areata.
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.
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.