Deep learning can improve non-invasive alopecia diagnosis using hair images.
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,
October 2023 Syntax-based neural networks can match Transformers in handling unseen sentences.
8 citations,
January 2022 in “Sensors” Deep learning can accurately automate hair density measurement, with YOLOv4 performing best.
Nonlinear artificial neural networks are better at identifying different types of animal hair than linear ones.
The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.
Transfer learning with three neural network architectures accurately classifies hair diseases.
April 2023 in “Journal of Investigative Dermatology” An automated method accurately assesses melanoma risk using 3D body images to analyze skin traits.
Pre-trained Transformers need extreme retraining to perform well on DarkNet data.
86 citations,
August 2021 in “Polymers” Microneedles are effective for drug delivery, vaccinations, fluid extraction, and treating hair loss, with advancements in manufacturing like 3D printing.
36 citations,
September 2015 in “Forensic Science International: Genetics” Certain DNA variants can predict straight hair in Europeans but are not highly specific.
November 2022 in “bioRxiv (Cold Spring Harbor Laboratory)” Using deep learning to predict gene expression from images could help assess colorectal cancer metastasis.
January 2021 in “Lecture notes in networks and systems” Deep learning can accurately detect Alopecia Areata with up to 98.3% accuracy.
101 citations,
January 1997 in “Journal of Investigative Dermatology Symposium Proceedings” Nerves and chemicals in the body can affect hair growth and loss.
October 2023 in “Sinkron” The system can accurately classify hair diseases with 94.5% accuracy using a CNN.
18 citations,
January 2020 in “Frontiers in Chemistry” A new model can predict drug-disease links well, helping drug research.
3 citations,
December 2018 in “Meta Gene” Certain gene variations increase male hair loss risk, influenced by hormone levels.
February 2024 in “Frontiers in physics” The new model detects hair clusters more accurately and efficiently, helping with early hair loss treatment and diagnosis.
10 citations,
September 2020 in “Computational and Mathematical Methods in Medicine” Researchers developed an algorithm for self-diagnosing scalp conditions with high accuracy using smart device-attached microscopes.
34 citations,
January 2020 in “IEEE Access” A model called PM-DBiGRU was developed for analyzing sentiments in drug reviews, and it performed better than other models, but struggled with complex sentences and situations requiring background knowledge.
December 2021 in “Acta dermato-venereologica” A deep learning model accurately predicts male hair loss types using scalp images.
7 citations,
January 2023 in “Frontiers in Cell and Developmental Biology” Caspases are enzymes important for both cell death and various non-lethal cell functions, affecting head development and hair growth, with different caspases playing specific roles.
228 citations,
September 2012 in “Trends in Neurosciences” Nerves are crucial for the regeneration of various body parts in many animals.
11 citations,
April 2013 in “SpringerPlus” Human skin's melanocytes respond to light by changing shape, producing pigments and hormones, which may affect sleep patterns.
64 citations,
March 2005 in “Journal of Investigative Dermatology” Brain-Derived Neurotrophic Factor (BDNF) slows down hair growth and promotes hair follicle regression.
4 citations,
January 2021 in “Dermatologic Therapy” AI is effective in diagnosing and treating hair disorders, including detecting hair loss and scalp conditions with high accuracy, but it should supplement, not replace, doctor-patient interactions.
1 citations,
February 2024 in “npj digital medicine” Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
1 citations,
January 2024 in “IEEE access” The new method improves facial image restoration quality and face recognition accuracy.
January 2024 in “Wiadomości Lekarskie” Robotic hair transplantation with AI offers more reliable, precise, and efficient hair restoration.
September 2023 in “International journal of medicine” AI is revolutionizing healthcare by improving diagnosis, treatment, and monitoring, but still needs close supervision.