research Innovations in skin microphysiological systems for nonclinical testing and FDA modernization
New technologies replicate human skin for testing without animals.
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480-510 / 1000+ resultsresearch Predicting Physical Appearance from Low Template: State of the Art and Future Perspectives
Machine learning improves DNA predictions for eye and hair color, but challenges remain for skin tone and facial features.
research Analyse trichoskopischer Bilder mit tiefen neuronalen Netzen zur Diagnose und Aktivitätsbewertung von Alopecia areata – eine retrospektive Studie
Deep-learning models can effectively diagnose and assess Alopecia areata using scalp images.
research From Diagnosis to Prognosis: A Scoping Review of Artificial Intelligence in Alopecia Research
AI in alopecia research needs better tools for predicting treatment outcomes and ensuring fairness.
research Analysis of modern approaches to hair care: An overview of products and techniques
Personalized hair care using modern techniques and science is essential for healthy hair.
research Efficient integration of human skin single-cell RNA sequencing data
A comprehensive human skin cell atlas was created to better understand skin biology and disease.
research Efficient integration of human skin single-cell RNA sequencing data
A comprehensive human skin cell atlas was created to better understand skin biology and disease.
research DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
research Analysis of modern approaches to hair care: An overview of products and techniques
Personalized hair care plans are essential for healthy hair.
research BaldPredict: AI-Driven Prediction Model for Alopecia Areata
AI can improve alopecia areata diagnosis with high accuracy.
research Genetic and Environmental Factors Affecting Hair Density in East Asian Populations
Age, sex, BMI, menopause, and specific genes affect hair density in East Asians.
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 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 A Segmental Approach to Scoring Hair Density from Global Images: Introducing the Scalp Coverage Scoring Method for Clinical Trials and Practice
The Scalp Coverage Scoring method reliably measures hair density from images.
research The role of 3Rs in the age of One Health: where we are and where we’re going
Innovative methods are reducing animal testing and improving biomedical research.
research Hair Disease Classification Using Convolutional Neural Network (CNN) Algorithm with VGG-16 Architecture
The system can accurately classify hair diseases with 94.5% accuracy using a CNN.
research Estimating Scalp Moisture in a Hat Using Wearable Sensors
A hat with sensors can measure scalp moisture well, helping with hair care.
research DEEP REVIEW ON ALOPECIA AREATA DIAGNOSIS FOR HAIR LOSS-RELATED AUTOIMMUNE DISORDER PROBLEM
Machine learning and deep learning can effectively diagnose alopecia areata.
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 Hair analysis based on medical history and spatial-temporal data
Machine learning can predict hair health accurately using personal data.
research In Search of Predictive Models for Inhibitors of 5-alpha Reductase 2 Based on the Integration of Bioactivity and Molecular Descriptors Data.
The models can help find better inhibitors for conditions like baldness and prostate disorders.
research Progesterone Promotes the Survival of Newborn Neurons in the Dentate Gyrus of Adult Male Mice
Progesterone helps adult male mice's brain cells survive and improves learning and memory.
research Prediction of therapeutic outcomes of female pattern hair loss patients based on clinical features with application of artificial intelligence
Artificial intelligence can accurately predict hair growth and treatment results in female pattern hair loss patients, with age of onset and duration being key factors.
research Anxiety-, and Depression-like Behaviour Following Short-Term Finasteride Administration is Associated with Impaired Synaptic Plasticity and Cognitive Behaviour in Male Rats
Short-term finasteride use in male rats caused anxiety, depression, and memory problems.
research Hair Color Digitization through Imaging and Deep Inverse Graphics
A new method accurately captures and renders hair color for real and synthetic images.
research Can online medical education improve management of challenging cases of onychomycosis?
Online medical education helps doctors make better clinical decisions and increases their knowledge in treating fungal nail infections.
research MachineLearning-Driven Optimization of TherapeuticSubstance Composition for High-Hardness, Fast-Dissolving Microneedlesfor Androgenetic Alopecia Treatment
Machine learning optimized microneedles promote hair regrowth better than minoxidil without safety risks.
research HERBSNAP: Advanced Classification of Bhringaraja and Honegone Herbal Species
Machine learning can accurately tell apart False Daisy and Smooth Joy Weed.
research 706 Predictive modeling of patient response to JAK/STAT inhibitors and dynamic patient-matching
Machine learning can predict how well patients with alopecia areata will respond to certain treatments.
research Neuropharmacological profile of Eclipta alba (Linn.) Hassk
Eclipta alba extract improved learning, memory, and stress-related ulcers in rats without affecting movement or causing anxiety.