October 2023 in “Sinkron” The system can accurately classify hair diseases with 94.5% accuracy using a CNN.
January 2021 in “Lecture notes in networks and systems” Deep learning can accurately detect Alopecia Areata with up to 98.3% accuracy.
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,
January 2023 in “IEEE access” Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
4 citations,
October 2022 in “Journal of Imaging” An intelligent system can classify hair follicles and measure hair loss severity with reasonable accuracy.
2 citations,
November 2021 in “Frontiers in Medicine” New skin imaging, teledermatology, and AI could become key in future dermatology care.
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.
September 2023 in “International journal of medicine” AI is revolutionizing healthcare by improving diagnosis, treatment, and monitoring, but still needs close supervision.
June 2023 in “International journal on recent and innovation trends in computing and communication” Combining multiple algorithms predicts hair fall more accurately than using single algorithms.
8 citations,
January 2022 in “Sensors” Deep learning can accurately automate hair density measurement, with YOLOv4 performing best.
7 citations,
September 2020 in “Bioscience Biotechnology and Biochemistry” The scalp has more diverse bacteria, while hair has more bacteria and unique types.
1 citations,
April 2023 in “Biomaterials advances” Gellan gum hydrogels help recreate the environment needed for hair growth cell function.
Transfer learning with three neural network architectures accurately classifies hair diseases.
1 citations,
April 2018 in “Lasers in Surgery and Medicine” New treatments and technologies in laser medicine show promise for improving skin conditions, fat reduction, cancer treatment, wound healing, and hair restoration.
9 citations,
January 2020 in “IEEE Access” The KEBOT system is a highly accurate AI tool for analyzing hair transplants.
January 2022 in “Journal of Pharmaceutical Negative Results” The VGG-SVM method accurately identifies and classifies stages of Alopecia Areata and other hair loss conditions.
The system can automatically identify different hair and scalp conditions using machine learning.
GoogLeNet is the best model for identifying folliculitis.