5 citations
,
February 2015 in “Dermatologica Sinica” Computer-aided imaging system helps measure balding area in female pattern hair loss.
2 citations
,
June 2020 in “Journal of Investigative Dermatology” 3D imaging of skin biopsies offers better accuracy but is time-consuming and can't clear melanin.
2 citations
,
September 2024 in “Diagnostics” A new method accurately measures cell changes in breast cancer.
January 2013 in “CINECA IRIS Institutial research information system (University of Pisa)”
January 2018 in “Surgical and Cosmetic Dermatology” The method is effective for evaluating hair loss treatments quickly and affordably.
16 citations
,
May 2023 in “Journal of the American Statistical Association” A new method makes analyzing large datasets with rare events faster and more efficient.
4 citations
,
May 2013 in “Dermatologic Surgery” Three new techniques simplify and improve the preparation of tissue samples for skin cancer surgery.
22 citations
,
May 2002 in “Skin Research and Technology” CE-PTG detects early hair follicle issues in balding areas, helping measure male hair loss.
1 citations
,
May 2016 in “Dermatologic Surgery” The document concludes that using a phototrichogram with a protractor and tapeline is a reliable and noninvasive way to measure hair loss.
January 2026 in “Archives of Dermatological Research” March 2019 in “Dermatologic Surgery”
April 2024 in “Clinical dermatology review (Print)” Trichoscopy is an effective, noninvasive method for early diagnosis of Female Pattern Hair Loss.
October 2024 in “Endocrinology Insights” The Bethesda system is effective for identifying thyroid cancer but has low sensitivity.
2 citations
,
July 2008 in “Dermatologic Surgery” The Cross-section Trichometer is a promising tool for measuring hair characteristics without cutting the hair and may have various clinical uses.
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.
The model accurately predicts hair breakage in Telogen Effluvium, aiding early detection and treatment.
17 citations
,
September 2022 in “Biomaterials Research” The film-trigger applicator improves microneedle skin delivery and drug efficiency using simple finger force.
1 citations
,
November 2020 in “bioRxiv (Cold Spring Harbor Laboratory)” Quantifying hair shape is better than using racial categories for understanding hair characteristics.
3 citations
,
January 2019 in “Electronic Imaging” The device accurately estimates natural hair color at the roots in real time.
November 2022 in “bioRxiv (Cold Spring Harbor Laboratory)” Using deep learning to predict gene expression from images could help assess colorectal cancer metastasis.
7 citations
,
August 2015 in “Dermatologic Surgery” The cross beam laser is a useful tool for safely measuring scalp stretchiness to improve hair transplant results.
2 citations
,
January 2024 in “IEEE Access” AlopeciaDet accurately detects Alopecia Areata early using advanced image analysis.
June 2022 in “Our Dermatology Online” Trichoscopy is essential for early detection and monitoring of female-pattern hair loss.
232 citations
,
January 2016 in “BMC Bioinformatics” The method can effectively extract biomedical information without needing expert annotation, performing better than previous models.
March 2024 in “medRxiv (Cold Spring Harbor Laboratory)” Recent selection on immune response genes was identified across seven ethnicities.
46 citations
,
April 2021 in “International Journal of Molecular Sciences” Curcumin shows promise in reducing pain and inflammation, but more research is needed.
November 2025 in “Indian Journal of Plastic Surgery” The new technique increases hair graft yield and minimizes scarring in hair restoration.
January 2024 in “Wiadomości Lekarskie” pbn-STAC effectively finds strategies for cellular reprogramming using deep reinforcement learning.
2 citations
,
September 2020 in “bioRxiv (Cold Spring Harbor Laboratory)” The laser system helps study brain cell functions by precisely removing specific cells and observing changes.
January 2026 in “JDDG Journal der Deutschen Dermatologischen Gesellschaft” Deep-learning models can effectively diagnose and assess Alopecia areata using scalp images.