research Enhanced stratification of male pattern hair loss using AI through novel loss region ratio analysis
AI improves accuracy and consistency in diagnosing male pattern hair loss.
Search
for
Sort by
Research
360-390 / 1000+ results research Recent advances in Forensic DNA Phenotyping of appearance, ancestry and age
Forensic DNA Phenotyping can now better predict appearance, ancestry, and age from DNA, but more research is needed for precise police use.
research Artificial intelligence in dermatology: а scoping review
AI in dermatology shows high accuracy in diagnosing skin diseases but needs more research for improvement.
research Characterizing enteric neurons in Dopamine Transporter (DAT)-Cre reporter mice reveals dopaminergic subtypes with dual-transmitter content
Dopaminergic neurons in the gut have distinct subtypes, some releasing both dopamine and acetylcholine.
research ScalpEye: A Deep Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health
ScalpEye accurately diagnoses scalp issues like dandruff and hair loss.
research A Combinatorial Tweet Clustering Methodology Utilizing Inter and Intra Cosine Similarity
The method effectively grouped tweets into categories without knowing the number of groups beforehand.
research Innovative approaches to baldness detection and management with artificial intelligence and machine learning
research 267 Deep phenotyping of patients with xeroderma pigmentosum and trichothiodystrophy
Deep phenotyping helps distinguish between xeroderma pigmentosum and trichothiodystrophy, aiding in diagnosis and treatment.
research FORENSIC DNA PHENOTYPING FOR CRIMINAL IDENTIFICATION
Forensic DNA phenotyping can now predict more physical traits and ancestry from DNA, but further improvements are needed.
research Enhancing Low-Light Sports Motion Images with Improved Bilateral Filtering and Auto MSRCR
The method greatly improves low-light sports images' quality and reduces artifacts.
research A novel predictive model for the recurrence of pediatric alopecia areata by bioinformatics analysis and a single-center prospective study
A new model uses specific blood markers to predict if children's hair loss will return.
research Prediction of cell states and key transcription factors of the human cornea through integrated single-cell omics analyses
A new tool accurately identifies human cornea cell states and key factors.
research Past, present, and future of global research on artificial intelligence applications in dermatology: A bibliometric analysis
AI in dermatology is growing rapidly, showing promise in diagnosing skin conditions as accurately as dermatologists.
research Assessment of college students’ mental health status based on temporal perception and hybrid clustering algorithm under the impact of public health events
A new method accurately measures college students' mental health by considering time perception and clustering techniques.
research A powerful method for pleiotropic analysis under composite null hypothesis identifies novel shared loci between Type 2 Diabetes and Prostate Cancer
New method finds genetic links between Type 2 Diabetes and Prostate Cancer not seen before.
research A Comparative Analysis of Large Language Model Accuracy for Image-Based Hair Disease Identification in Diverse Skin Tones
ChatGPT is more accurate at diagnosing hair disorders in lighter skin tones than darker ones.
research An Expert System for Clinical Risk Assessment of Polycystic Ovary Syndrome under Uncertainty
The document concludes that the new expert system can assess the risk of PCOS effectively despite uncertainties in diagnosis.
research Hair Loss Diagnosis Using Artificial Neural Networks
Neural networks can effectively predict hair loss.
research Integrated edge information and pathway topology for drug-disease associations
iEdgePathDDA effectively finds new drug-disease links, outperforming other methods.
research 198 Reliable and interpretable segmentation for remote assessment of atopic dermatitis severity using digital images
The improved EczemaNet more reliably and clearly identifies and assesses the severity of atopic dermatitis from photos.
research Characterizing enteric neurons in dopamine transporter (DAT)‐Cre reporter mice reveals dopaminergic subtypes with dual‐transmitter content
Dopaminergic neurons in the gut have diverse subtypes with different neurotransmitter contents.
research Automating Hair Loss Labels for Universally Scoring Alopecia From Images
The AI system HairComb accurately scores hair loss severity, matching dermatologist assessments.
research Forensic DNA phenotyping: A promising tool to predict human appearance for forensic purposes
Forensic DNA phenotyping can predict physical traits from DNA but faces challenges in knowledge and ethics.
research AI06 ALUDWIG: an automated artificial intelligence-based assessment of female androgenic alopecia
ALUDWIG can help standardize female hair loss assessment from a single image.
research Chaos and antichaos in pathology
Understanding chaos and control mechanisms in disease can improve diagnosis and prediction in medicine.
research Mind the Gap: A Solution to the Robustness Problem of Turing Patterns Through Patterning Mode Isolation
Pattern mode isolation improves the reliability and predictability of Turing patterns.
research Modeling Dynamic Hair as a Continuum
The authors created a realistic and efficient method to simulate hair movement by combining fluid dynamics with individual hair strand behavior.
research Use of Single‐Cell Data and scPagwas Analysis to Identify T Cell Subsets and Construct a Prognostic Model for Clear Cell Renal Cell Carcinoma
T cell subsets are crucial in kidney cancer, and a new model predicts patient outcomes using key genes.
research A Genome-Wide Association Study and Machine-Learning Algorithm Analysis on the Prediction of Facial Phenotypes by Genotypes in Korean Women
The model accurately predicts skin conditions in Korean women using genetic information, aiding personalized skincare.
research An Analysis of Alopecia Areata Classification Framework for Human Hair Loss Based on VGG-SVM Approach
The VGG-SVM method accurately identifies and classifies stages of Alopecia Areata and other hair loss conditions.