research Predicting Human Appearance from DNA for Forensic Investigations
DNA can predict physical traits like eye and hair color accurately, especially in Europeans, but predicting other traits and in diverse populations needs more research.
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research Digit-length ratios (2D:4D) as a phenotypic indicator of in utero androgen exposure is not prognostic for androgenic alopecia: a descriptive-analytic study of 1200 Iranian men
Finger length ratios don't predict baldness in men.
research 5α-Reductase Inhibitors, Chemical and Clinical Models
Researchers developed a model to predict how well certain compounds can block an enzyme related to hair loss and prostate issues, suggesting a 50 mg dose of finasteride might be effective based on lab and body data.
research Charting the Bromodomain BRD4: Towards the Identification of Novel Inhibitors with Molecular Similarity and Receptor Mapping
Researchers identified promising inhibitors for the BRD4 protein, including finasteride and amentoflavone.
research Optimized VGG19 Architecture for Precise and Efficient Multi-Class Hair Disease Classification
The optimized VGG19 model accurately classifies hair diseases with 98.64% accuracy.
research Utility of caffeine analysis for forensic hair discrimination
Caffeine in hair might help identify people, but it's not always reliable.
research Minimizing Factual Inconsistency and Hallucination in Large Language Models
A new method improves the accuracy and reliability of language models by up to 42%.
research Scalp Disorder Imaging: How Deep Learning and Explainable Artificial Intelligence are Revolutionizing Diagnosis and Treatment
Deep learning and explainable AI are improving scalp disorder diagnosis, but challenges in transparency and data quality remain.
research Harnessing Deep Learning for Scalp and Hair Disease Classification: A Comparative Study of Convolutional Neural Networks Architectures
VGG16 and VGG19 are the most accurate for classifying scalp and hair diseases.
research Poster Abstracts
The model and estimator can predict drug exposure in kidney transplant patients well.
research Convolutional Neural Networks for Non-Invasive Diagnosis of Androgenetic Alopecia using Dermoscopic Hair Images
Deep learning can improve non-invasive alopecia diagnosis using hair images.
research Identification of Stress-Related Hair Loss and Prevention Through the Application of a KNN Model Based on Machine Learning
Machine learning can predict stress-related hair loss and suggest prevention tips.
research The Black identity, hair product use, and breast cancer scale
The BHBS is a valid tool to study cultural norms and breast cancer risk in Black women.
research Determining the Relationship Among Cattle Genotype, Hair Coat Score, and Productivity Through the Investigation of Single Nucleotide Polymorphisms within Prolactin, Dopamine Receptor D2, and Melatonin Receptor 1A
research Digital measurement of melasma: Towards eliminating subjectivity from treatment evaluation
The digital system for measuring melasma shows promise but needs more development for better accuracy and automation.
research The Use of 2D: 4D Digit Ratio as a Predictor of Androgenetic Alopecia: A Review
Finger length ratios might help predict common hair loss.
research Quantitative analysis and development of alopecia areata classification frameworks
A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.
research A Tale of Two Haplotypes: The EDA2R/AR Intergenic Region is the Most Divergent Genomic Segment between Africans and East Asians in the Human Genome
The most different genetic segment between Africans and East Asians is the EDA2R/AR region, with two main types influenced by population changes and natural selection, and linked to baldness.
research Pharmacophore Modeling and Three Dimensional Database Searching for Drug Design Using Catalyst: Recent Advances
The document concludes that Catalyst software is effective for drug design, identifying potent compounds for various medical conditions.
research Analysing the dynamics of a model for alopecia areata as an autoimmune disorder of hair follicle cycling
The model helps understand and improve treatments for alopecia areata by simulating hair growth and immune cell interactions.
research New clinico‐genetic classification of trichothiodystrophy
A new classification for trichothiodystrophy helps identify genetic causes and potential treatments.
research NUMERICAL DESCRIPTOR COMPUTATION OF ALOPECIA DRUGS USING COM – POLYNOMIAL
Numerical methods help analyze alopecia drugs' properties effectively.
research The substantial role of asymmetric hair follicle differentiation in determining hair shape with ethical/racial related diversity
Asymmetric hair follicle differentiation causes the unique shape of kinky hair.
research Rac-dependent signaling from keratinocytes promotes differentiation of intradermal white adipocytes
Signals from skin cells controlled by Rac proteins help turn certain precursor cells into white fat cells.
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.
research Trichothiodystrophy and fragile hair: the distinction between diagnostic signs and diagnostic labels in childhood hair disease
research Simultaneous Target-Mediated Drug Disposition-Pharmacodynamic (TMDD-PD) Modeling of Finasteride and Dutasteride: Impact of Target Binding and Turnover on Non-linear Pharmacokinetics
Finasteride and dutasteride's effects are mainly due to target binding saturation and slow enzyme turnover.
research Trichoscopic criteria of different stages of male pattern hair loss
Trichoscopy effectively distinguishes between severe and mild male pattern hair loss.
research Association of atopic dermatitis with autoimmune diseases: A bidirectional and multivariable two-sample mendelian randomization study
Atopic dermatitis increases the risk of some autoimmune diseases.
research An Improved Face Image Restoration Method Based on Denoising Diffusion Probabilistic Models
The new method improves facial image restoration quality and face recognition accuracy.