An automated system can accurately classify hair disorders using image analysis.
28 citations
,
February 2020 in “Clinical Ophthalmology” Certain medications and patient factors increase the risk of Intraoperative Floppy Iris Syndrome during cataract surgery, but with careful planning and technique adjustments, complications can be minimized.
3 citations
,
March 2000 in “Journal of the American Academy of Dermatology” The atlas is a useful, affordable guide for skin disease pathology, despite lacking color images.
12 citations
,
July 2011 in “European Journal of Dermatology” The VSCAPSI is a helpful method for evaluating the severity of scalp psoriasis.
3 citations
,
November 2017 in “The American Journal of Cosmetic Surgery” The new Cosmetic Surgery Scar Assessment Scale (CSSAS) was found to be simple and effective in evaluating scars from hair restoration surgeries.
2 citations
,
December 2021 The research found that the properties of solid-state Electronic Circular Dichroism (ss-ECD) are influenced by the orientation of local crystals, which could help in examining and mapping chiral materials like pharmaceutical ingredients.
August 2024 in “Nihon Ika Daigaku Igakkai Zasshi” The study made scar tissue transparent to better understand its structure.
37 citations
,
December 2014 in “Journal of Biomedical Informatics” Researchers created LabeledIn, a detailed list of drug uses, showing the importance of human input in making such lists.
April 2023 in “Journal of Investigative Dermatology” An automated method accurately assesses melanoma risk using 3D body images to analyze skin traits.
46 citations
,
July 2008 in “Dermatologic Therapy” A scale was made to measure hair loss severity in African American women.
February 2026 in “Cureus” Two methods reliably measure scalp area and hair count.
February 2024 in “arXiv (Cornell University)” Adjusting AI training data for skin condition distribution improves accuracy across different clinical settings.
June 2025 in “British Journal of Dermatology” ALUDWIG can help standardize female hair loss assessment from a single image.
The model accurately identifies hair diseases using deep learning.
July 2007 in “Hair transplant forum international” 3 citations
,
October 2011 The updated criteria improve the accuracy of diagnosing lupus.
9 citations
,
January 2021 in “Biomolecules” Infrared spectral imaging can map hair growth proteins and sugars without staining.
September 2025 in “International Journal of Dermatology” February 2025 in “International Journal of Dermatology” August 2020 in “International Journal of Dermatology” January 2018 in “International Journal of Dermatology”
42 citations
,
January 2011 in “Journal of Biomedical Optics” Infrared and Raman imaging can non-destructively analyze hair structure and help diagnose hair conditions.
November 2025 in “Scientific Reports” AI improves accuracy and consistency in diagnosing male pattern hair loss.
November 2022 in “Zenodo (CERN European Organization for Nuclear Research)” April 2019 in “The journal of investigative dermatology/Journal of investigative dermatology” Higher resolution images are needed to identify scarring and fine hair in alopecia.
9 citations
,
January 2011 in “Skin Research and Technology” The new automatic tool accurately measures hair thickness and is reliable.
3D models from confocal microscopy improve melanoma detection on sun-damaged skin.
5 citations
,
March 2017 in “Laser Physics Letters” Different scalp imaging methods are important for studying hair and scalp health and require more volunteers for better evaluation.
19 citations
,
October 2024 in “BMC Medical Informatics and Decision Making” AI can improve early diagnosis and classification of PCOS, aiding in prevention of related health issues.
May 2017 in “Hair transplant forum international” The event was a significant and transformative experience in the field of hair transplantation.