November 2023 in “The journal of investigative dermatology/Journal of investigative dermatology” Skin cells and certain hair follicle areas produce hemoglobin, which may help protect against oxidative stress like UV damage.
August 2023 in “Processes” Fermenting Dendrobium officinale with Lactobacillus reuteri CCFM8631 increases its skin care benefits.
Plant-based compounds can improve wound dressings and skin medication delivery.
May 2023 in “Journal of Investigative Dermatology” Blocking DPP4 can potentially speed up hair growth and regeneration, especially after injury or in cases of hair loss.
May 2023 in “BMC Women's Health” Many women who have used performance-enhancing drugs in Finland show high rates of mental health and substance use issues, and most have normal red blood cell counts.
January 2023 in “Burns & Trauma” The study concluded that the new wound model can be used to evaluate skin regeneration and nerve growth.
September 2022 in “Frontiers in Bioengineering and Biotechnology” Taxifolin from Rhododendron mucronulatum may help prevent hair loss and promote hair growth.
May 2022 in “Journal of the Dermatology Nurses' Association” The convention highlighted the importance of comprehensive patient care and early diagnosis in dermatology.
April 2007 in “CRC Press eBooks” Certain vitamins in wrong amounts, alcohol abuse, metals, and other toxins can cause serious brain and nerve damage.
215 citations,
March 2011 in “Clinical Cancer Research” Sorafenib is effective in treating Desmoid Tumor/Deep Fibromatosis.
37 citations,
October 2017 in “Advanced drug delivery reviews” The review suggests that there are various treatments to help restore skin color after severe burns.
33 citations,
April 2017 in “American journal of clinical dermatology” Early treatment of superficial fungal infections in immunocompromised patients is crucial.
11 citations,
October 2017 in “Mycoses” An 80-year-old man's deep beard infection was cured with oral terbinafine after identifying the fungus Trichophyton verrucosum.
8 citations,
January 2022 in “Sensors” Deep learning can accurately automate hair density measurement, with YOLOv4 performing best.
6 citations,
January 2021 in “Frontiers in Immunology” Certain immune cells worsen post-surgery gut paralysis by activating a specific immune response.
1 citations,
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,
January 2023 in “IEEE access” Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
1 citations,
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.
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.
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.