June 2021 in “Cosmoderma” Hair transplantation techniques have improved, making the process safer and more effective with less visible scarring.
January 2017 in “Indian journal of health sciences and biomedical research KLEU” There is no link between hair loss and prostate enlargement.
January 2004 in “Indian Journal of Nephrology”
419 citations,
January 2015 in “Journal of Consumer Research” Corporate social responsibility can improve consumer ratings of product performance, especially when the company is seen as benevolent and consumers aren't experts on the product.
93 citations,
January 2016 in “British Journal of Dermatology” Eating a high-glycemic diet may worsen acne by increasing certain protein levels and expressions in the skin.
5 citations,
August 2013 in “Facial plastic surgery clinics of North America” Use a frontal forelock pattern to manage advanced hair loss.
4 citations,
December 2009 in “Current Medical Research and Opinion” Dermatologists are more comfortable and proactive in treating male pattern hair loss than primary care physicians.
August 2024 in “Frontiers in Pharmacology” Antibody treatments show promise for hair loss but need more research.
October 2017 in “Springer eBooks” A thorough initial check-up is essential before sperm banking to ensure the best chance of preserving good quality sperm.
12 citations,
February 2019 in “Journal of patient-reported outcomes” Patients with HR+/HER2- advanced breast cancer commonly experience fatigue, hair loss, and pain, which significantly affect daily activities.
10 citations,
September 2022 in “Journal of Biophotonics” Blue light therapy is safe for skin and may protect against UV radiation.
1 citations,
August 2023 in “Advanced Drug Delivery Reviews” Microneedles are promising for long-acting drug delivery and can improve patient compliance, but more data is needed to confirm their effectiveness.
86 citations,
October 2005 in “Experimental Dermatology” The Foxn1 gene mutation causes hairlessness and immune system issues, and understanding it could lead to hair growth disorder treatments.
4 citations,
July 2022 in “International Journal of Cosmetic Science” Hair moisture behavior helps tell apart different chemical treatments and reveals insights into hair structure.
1 citations,
July 2019 in “Journal of the Dermatology Nurses' Association” The author found the Dermatology Nurses’ Association’s annual meeting valuable for both learning and making friends.
Transfer learning with three neural network architectures accurately classifies hair diseases.
June 2001 in “International Journal of Cosmetic Surgery and Aesthetic Dermatology” The Hair Implanter Pen increases speed and is gentle on grafts, with users mastering it after a few tries.
3 citations,
October 2022 in “Nano Letters” Machine learning identified promising nanozymes for treating hair loss.
The model accurately classifies hair conditions with 97% accuracy.
October 2023 in “Journal of the Endocrine Society” Machine learning identified three unique subtypes of androgen excess in women with PCOS, each with different metabolic risks.
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.
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.
June 2022 in “Frontiers in Genetics” Machine learning is effective in predicting gene functions and their relationships with diseases.
January 2021 in “Lecture notes in networks and systems” Deep learning can accurately detect Alopecia Areata with up to 98.3% accuracy.
September 2017 in “Indian Journal of Plastic Surgery” Garg and Garg created an affordable, easy-to-use training program for hair restoration surgery using everyday items, which can teach a technician the basics in 3-4 weeks with two hours of daily practice.
December 2021 in “Acta dermato-venereologica” A deep learning model accurately predicts male hair loss types using scalp images.
232 citations,
January 2016 in “BMC Bioinformatics” The method can effectively extract biomedical information without needing expert annotation, performing better than previous models.
8 citations,
August 2020 in “PLOS Computational Biology” A machine learning model called CATNIP can predict new uses for existing drugs, like using antidepressants for Parkinson's disease and a thyroid cancer drug for diabetes.
3 citations,
January 2023 in “European Journal of Information Technologies and Computer Science” The machine learning model accurately detected hair loss and scalp diseases using processed images.