1 citations
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March 2024 in “Skin research and technology” A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.
1 citations
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March 2024 in “arXiv (Cornell University)” Deep learning can effectively detect hair and scalp diseases early.
1 citations
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August 2023 in “arXiv (Cornell University)” Deep learning effectively diagnoses scalp disorders, but improvements are needed.
1 citations
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January 2023 in “IEEE access” Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
1 citations
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February 2004 in “Dermatologic Surgery” Deep Plane Fixation in scalp surgeries allows for more tissue removal with less tension, leading to better healing and less scarring.
March 2026 in “ACS Applied Materials & Interfaces” A new dissolving microneedle system effectively delivers minoxidil for hair regrowth with minimal side effects.
The system effectively detects scalp diseases and classifies hair fall stages with high precision.
November 2025 in “Analytical Chemistry” A new method improves protein extraction from hair, helping identify potential biomarkers for fetal growth issues.
November 2025 in “OPAL (Open@LaTrobe) (La Trobe University)” A new method helps find proteins in hair to identify fetal growth issues.
October 2025 in “Chinese Chemical Letters” Using a special solvent can make Cacumen Platycladi essential oil more effective for treating hair loss.
The model accurately predicts hair loss severity in alopecia areata.
July 2025 in “The Ewha Medical Journal” The model accurately detects early-stage hair loss using images.
June 2025 in “Indian Journal of Veterinary Medicine” The dog's skin infection was cured with a new antibiotic treatment and supplements.
The model accurately diagnoses hair diseases with 95% accuracy using deep learning.
January 2025 in “Communications in computer and information science” HairLossMultinet accurately classifies hair damage with 98% accuracy but needs a more diverse dataset for broader use.
September 2024 in “Journal of Investigative Dermatology” A new tool can analyze hair to detect changes due to hormones, genetics, and aging.
The model accurately classifies hair conditions with 97% accuracy.
January 2024 in “International Journal of Advanced Computer Science and Applications” Deep learning and explainable AI are improving scalp disorder diagnosis, but challenges in transparency and data quality remain.
January 2024 in “Wiadomości Lekarskie” pbn-STAC effectively finds strategies for cellular reprogramming using deep reinforcement learning.
Deep eutectic solvents can replace toxic solvents in extracting useful compounds for medicines.
GoogLeNet is the best model for identifying folliculitis.
May 2023 in “Indian journal of science and technology” The new deep learning system can accurately recognize hair loss conditions with a 95.11% success rate.
March 2023 in “Applied and Computational Engineering” Deep learning models can analyze scalp diseases effectively.
December 2022 in “Research Square (Research Square)” The document concludes that an automatic system using deep learning can help diagnose skin disorders, but challenges and opportunities in this area remain.
November 2022 in “PubMed” Deep dermal tissue dislocation injury in pigs leads to thicker fibrotic tissue and increased type III collagen, affecting skin repair.
September 2022 in “Research Square (Research Square)” The AI model DIET-AI effectively diagnoses skin diseases as well as doctors.
July 2022 in “International Journal of Applied Pharmaceutics” Machine learning and deep learning can effectively diagnose alopecia areata.
January 2021 in “Lecture notes in networks and systems” Deep learning can accurately detect Alopecia Areata with up to 98.3% accuracy.
April 2017 in “Journal of Investigative Dermatology” Deep phenotyping helps distinguish between xeroderma pigmentosum and trichothiodystrophy, aiding in diagnosis and treatment.
February 2004 in “Dermatologic Surgery” Deep Plane Fixation in scalp surgeries allows for more tissue removal with less tension and minimal scarring.