research Continuous Dynamics of The Hair Follicle: Spiral Model for Understanding Follicular Activity Throughout Life
The Spiral Model helps understand hair growth changes with age and identify hair problems early.
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960-990 / 1000+ results research A Modeling Conundrum: Murine Models for Cutaneous Wound Healing
Current murine models need improvement for better human wound healing research translation.
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 Assessment of Multidimensional Health Care Parameters Among Adults in Japan for Developing a Virtual Human Generative Model: Protocol for a Cross-sectional Study (Preprint)
The study aims to create a model to improve personalized and preventive health care.
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 Modeling the Psychiatric Aspects of Polycystic Ovary Syndrome and Induced Stress
Stress and PCOS together may increase depression and anxiety-like behaviors.
research Hair keratin molecular dynamics models
Molecular dynamics simulations help understand keratin's properties and predict hair's response to treatments.
research A weighted non-negative matrix factorization approach to predict potential associations between drug and disease
WNMFDDA effectively predicts drug-disease associations.
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 A 3D microtumour system that faithfully represents ovarian cancer minimal residual disease
The study developed a 3D model that closely imitates remaining ovarian cancer after treatment and identified a potential drug targeting resistant cancer cells.
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 Hair keratin molecular dynamics studies
Simulations of hair keratin help improve disease treatment and cosmetic products.
research Early prediction of alopecia areata using machine learning modeling of neuro stress immune signatures from multi datasets
A machine learning model can predict alopecia areata early using specific gene markers.
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 QSAR Analysis of a Series of Hydantoin‐based Androgen Receptor Modulators and Corresponding Binding Affinities
Researchers developed reliable models to predict how well certain compounds bind to androgen receptors, emphasizing the importance of atomic electronegativity.
research A Model for Predicting Polycystic Ovary Syndrome Using Serum AMH, Menstrual Cycle Length, Body Mass Index and Serum Androstenedione in Chinese Reproductive Aged Population: A Retrospective Cohort Study
A model using hormone levels, cycle length, and BMI can help identify PCOS in Chinese women but isn't for screening teens.
research Pharmacophore and Atom Based 3D QSAR Studies on the Novel 5-Alpha-Reductase Inhibitors
The developed model can predict effective 5-alpha-reductase enzyme inhibitors.
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 Pharmacophore Models for Toxicology Prediction
Pharmacophore models can predict liver toxicity and central nervous system toxicity, but they have limitations and specific requirements.
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.
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 The Follicle Inference Engine (FIE): A stochastic digital twin and optimal experimental design framework for androgenetic alopecia
research Balancing metabolic optimization and reproductive safety in Polycystic Ovary Syndrome: a Bayesian-informed framework for GLP-1 receptor agonists
research Experimental Models and Molecular Pathogenesis: An Integrated Review of Alopecia
Current models for studying alopecia are inadequate, and more human-like systems are needed.
research Analysis of Animal Models of Alopecia Areata(AA) Based on Clinical Features of Traditional Chinese and Western Medicine
Better models and evaluation methods for alopecia areata are needed.
research Assessment of Multidimensional Health Care Parameters Among Adults in Japan for Developing a Virtual Human Generative Model: Protocol for a Cross-sectional Study
The study aims to create a model to predict health attributes using diverse health data from Japanese adults.
research Signal Peptide-CUB-EGF-like Domain-Containing Protein 3 (SCUBE3): From Molecule to Therapy
SCUBE3 is a potential target for cancer and alopecia treatment but is challenging to target due to its varied roles.
research Multi-scale modeling for cell fate specification during regeneration and development
Signaling factors and gene-driven cell adhesion are crucial for wound healing and embryo development.
research Open and Closed Structure
The 3D hair follicle model improves understanding of hair growth and drug testing.
research A machine learning and network framework to discover new indications for small molecules
A machine learning model called CATNIP can predict new uses for existing drugs, like using antidepressants for Parkinson's disease and a thyroid cancer drug for diabetes.