Deep learning can improve non-invasive alopecia diagnosis using hair images.
April 2023 in “Journal of Investigative Dermatology” An automated method accurately assesses melanoma risk using 3D body images to analyze skin traits.
1 citations,
February 2024 in “npj digital medicine” Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
April 2021 in “Journal of Investigative Dermatology” Spironolactone safely and effectively treats hair loss in female scarring alopecia patients.
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.
The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.
August 2024 in “Biomolecules & Therapeutics” A new compound, HTPI, promotes hair growth by protecting cells from damage and regulating energy use.
The model accurately classifies hair conditions with 97% accuracy.
GoogLeNet is the best model for identifying folliculitis.
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 2024 in “Journal of Investigative Dermatology” A new tool can analyze hair to detect changes due to hormones, genetics, and aging.
July 2024 in “International Journal of Molecular Sciences” The inhibitor DPP can promote hair growth.