research Genetic prediction of male pattern baldness based on large independent datasets
New models predict male pattern baldness better than old ones but still need improvement.
Search
for
Sort by
Research
270-300 / 1000+ results 
research Forensic DNA Phenotyping: a review on SNP panels, genotyping techniques, and prediction models
Forensic DNA phenotyping faces challenges due to inconsistent terminology, limited genetic understanding, and debates over technology and models.
research Hair Follicle Classification and Hair Loss Severity Estimation Using Mask R-CNN
An intelligent system can classify hair follicles and measure hair loss severity with reasonable accuracy.
research HairSentinel: a time-aware anomaly detection framework for forecasting hairfall trends using temporal fusion transformers
"HairSentinel" accurately detects hairfall trends using simple user data, helping identify health risks early.
research Forensic DNA phenotyping: a review on SNP panels, genotyping techniques, and prediction models
Forensic DNA phenotyping faces challenges like inconsistent terms and limited genetic knowledge.
research LB1040 Machine learning-based predictive model with routine blood work identifies moderate-severe alopecia areata
Machine learning can use blood tests to help predict moderate-to-severe alopecia areata.
research Analyzing Big EHR Data—Optimal Cox Regression Subsampling Procedure with Rare Events
A new method makes analyzing large datasets with rare events faster and more efficient.
research Expert Consensus on Big Data Collection of Skin and Appendage Disease Phenotypes in Chinese
research A Data-Driven Approach to Polycystic Ovary Syndrome Diagnosis: Evaluating Machine Learning Models
Machine learning can improve early and accurate detection of PCOS.
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 Artificial Intelligence in Dermatology: Assessing Predictability in Clinical Diagnosis
The AI showed high accuracy in diagnosing skin conditions but needs improvement for immunological and infectious disorders.
research Phenotype-Specific Lifestyle Prediction for PCOS Using Machine Learning Multi-Class Classification and SHAP Explainability
Machine learning can accurately predict PCOS phenotypes using lifestyle and symptom data.
research A Powerful Method for Pleiotropic Analysis under Composite Null Hypothesis Identifies Novel Shared Loci Between Type 2 Diabetes and Prostate Cancer
The new method found new shared genetic areas linked to both Type 2 Diabetes and Prostate Cancer.
research Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modeling of human appearance traits
Using trait prevalence priors in genetic prediction models for appearance traits is currently impractical due to limited knowledge and potential accuracy issues.
research 42063 Image Quality Assessment using Convolutional Neural Network in Clinical Skin Images
The model can effectively identify good quality skin images but needs more testing for real-world use.
research The Follicle Inference Engine (FIE): A stochastic digital twin and optimal experimental design framework for androgenetic alopecia
research A Novel Fusion Technique for Early Detection of Alopecia Areata Using ResNet-50 and CRSHOG
AlopeciaDet accurately detects Alopecia Areata early using advanced image analysis.
research Hair color digitization through imaging and deep inverse graphics
A new method accurately captures and renders hair color for virtual reality and hair dye use.
research Studying Hair Growth Cycle and its Effects on Mouse Skin
Understanding the hair growth cycle in mice is crucial for accurate research, as it affects study results and requires careful timing and methods.
research 309 DOES VARIATION IN EITHER AGE AT START OF THERAPY OR DURATION OF THERAPY MAKE CHEMOPREVENTION WITH FINASTERIDE COST-EFFECTIVE?
Starting finasteride at age 65 and continuing until age 80 is the most cost-effective strategy for prostate cancer prevention.
research Minoxidil, Platelet-Rich Plasma (PRP), or Combined Minoxidil and PRP for Androgenetic Alopecia in Men: A Cost-Effectiveness Markov Decision Analysis of Prospective Studies
Minoxidil alone is the most cost-effective treatment for male hair loss at a $50,000 threshold.
research USO DE ESTIMULAÇÃO CEREBRAL PROFUNDA (DBS) PARA O TRATAMENTO DA DOENÇA DE PARKINSON
Deep Brain Stimulation helps manage Parkinson's symptoms when medication isn't enough.
research Analysis of the human diseasome using phenotype similarity between common, genetic and infectious diseases
The study found that diseases can be grouped by symptoms and that the accuracy of predicting disease-related genes varies with the data source.
research scINSIGHT for interpreting single-cell gene expression from biologically heterogeneous data
scINSIGHT accurately identifies cell clusters and gene patterns in complex data.
research GAN-Based ROI Image Translation Method for Predicting Image after Hair Transplant Surgery
The new method predicts post-hair transplant images more accurately than other methods.
research Forensic DNA Phenotyping
Forensic DNA Phenotyping accurately predicts physical traits and is used in investigations, but needs more diverse population data for confirmation.
research Accuracy of Generative AI Chatbots in Answering Plastic Surgery Examination Questions: A Comparative Evaluation of ChatGPT‐4o, Gemini Advanced, and DeepSeek‐R1
AI chatbots can be reliable learning tools for plastic surgery students.
research Coupled 3D reconstruction of sparse facial hair and skin
The new algorithm accurately captures both facial hair and skin in 3D using a camera-based system.
research The Hair Cell Analysis Toolbox: A machine learning-based whole cochlea analysis pipeline
The Hair Cell Analysis Toolbox automates and improves the analysis of cochlear hair cells using machine learning.