research Deep Learning-based Trichoscopic Image Analysis and Quantitative Model for Predicting Basic and Specific Classification in Male Androgenetic Alopecia
A deep learning model accurately predicts male hair loss types using scalp images.
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research Prediction of male-pattern baldness from genotypes
Genetic data can predict male-pattern baldness with moderate accuracy, especially for early-onset cases in some European men.
research Alopecia and severity of COVID-19: a cross-sectional study in Peru
Men with hair loss are more likely to experience moderate to severe COVID-19 symptoms.
research Serum-Based Assessment of Alopecia Areata Response to Treatment Using ATR-FTIR Spectroscopy
ATR-FTIR spectroscopy could help monitor alopecia areata treatment response non-invasively.
research Prediction of Alopecia Areata using CNN
A new CNN model can detect Alopecia Areata with 98% accuracy.
research LEVERAGING MACHINE LEARNING METHODS IN PREDICTING AND ANALYZING THE ASSOCIATION BETWEEN DIETARY INFLAMMATORY INDEX AND ALOPECIA
Inflammatory diets may increase the risk and severity of alopecia areata.
research Smart Diagnostic System for Health Risk Assessment
WomenCare helps predict PCOD risk in women to encourage early medical consultation.
research An Approach to Detect Alopecia Areata Hair Disease Using Deep Learning
Deep learning can accurately detect Alopecia Areata with up to 98.3% accuracy.
research Predictive Modeling of Hair Fall using Random Forest Algorithms
The model accurately predicts hair loss by analyzing various factors.
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 Automated Monkeypox Identification from Electronic Medical Records Using Large Language Models — Shenzhen City, Guangdong Province, China, 2023–2025
Large language models can accurately identify monkeypox from medical records.
research Incidence of alopecia in brain tumour patients treated with pencil scanning proton therapy and validation of existing NTCP models
A standardized scoring system is needed to improve model reliability for predicting hair loss in brain tumor patients treated with proton therapy.
research Optimized polycystic ovarian disease prognosis and classification using AI based computational approaches on multi-modality data
AI can improve early diagnosis and classification of PCOS, aiding in prevention of related health issues.
research Severity Prediction of Hair Loss in Alopecia Areata with Hybrid Deep Learning Architecture
The model accurately predicts hair loss severity in alopecia areata.
research Epigenetic age estimation in saliva and in buccal cells
The model accurately predicts age from saliva and buccal cells for forensic use.
research Evaluation of loci to predict ear morphology using two SNaPshot assays
Genetic markers can help predict ear shapes for forensic use.
research An Analysis of the Correlation between Alopecia and Chief Complaints
Hair loss is significantly linked to symptoms like dry hair, scalp issues, addiction to tobacco or coffee, anxiety, and digestive problems.
research Applying Machine Learning Technique on Registry Data to Assess Factors Associated With In-Hospital Mortality Among STEMI Patients With Hypertension
Age, diabetes, and cardiogenic shock at PCI are key factors linked to in-hospital death in STEMI patients with hypertension.
research Polycystic ovarian syndrome: Prevalence and its correlates among adolescent girls
About 15% of adolescent girls in a region of India have Polycystic Ovarian Syndrome, which is more common in those born by cesarean, with wisdom teeth, or with central obesity.
research A Fuzzy Logic-Based Computational Framework for Precision Triage in Androgenetic Alopecia: A Simulated Biomarker-Driven Approach
The TPAP method effectively categorizes androgenetic alopecia patients with high accuracy, but needs real-world validation.
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 Bayesian measurement-error-driven hidden Markov regression model for calibrating the effect of covariates on multistate outcomes: Application to androgenetic alopecia
Model improves accuracy in predicting hair loss effects.
research Effect of Behavioral Factors on Severity of Female Pattern Hair Loss: An Ordinal Logistic Regression Analysis
Avoid alcohol, ponytails, and oily scalp, and get good sleep to prevent severe hair loss.
research Comparison of In Vitro Fertilization/Intracytoplasmic Sperm Injection Cycle Outcome in Patients with and without Polycystic Ovary Syndrome: A Modified Poisson Regression Model.
Women with PCOS have a similar chance of getting pregnant using assisted reproductive treatment as those without PCOS.
research Comparative Evaluation of Buffy Coat–Derived and Apheresis Platelet-Rich Plasma in the Treatment of Androgenetic Alopecia: Laboratory and Clinical Insights
Buffy coat PRP is more effective for hair growth in androgenetic alopecia than apheresis PRP.
research Peer Review #6 of "The mediation role of sleep on the relationship between drinks behavior and female androgenetic alopecia (v0.2)"
Sleep may mediate the link between sugary drinks and female hair loss.
research Hyperpigmentation post laser hair removal in patients taking Vitamin D supplements
Taking Vitamin D supplements may increase the risk of skin darkening after laser hair removal.
research Population exposure–response analysis of the effect of ritlecitinib on eyebrow assessment and eyelash assessment in patients with alopecia areata
Ritlecitinib effectively regrows eyebrow and eyelash hair in alopecia areata, with 50 mg being the best dose.
research Evaluation of affective temperament and anxiety–depression levels of patients with polycystic ovary syndrome
Women with PCOS tend to have higher anxiety and depression levels compared to healthy women.
research Comparative Analysis of Machine Learning Algorithms in Diagnosis of Polycystic Ovarian Syndrome
The Random Forest algorithm was the most accurate at diagnosing Polycystic Ovarian Syndrome.