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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 A systematic simulation-based meta-analytical framework for prediction of physiological biomarkers in alopecia
The study identified 12 potential biomarkers for hair loss and how they affect hair growth.
research 62202 Network meta-analysis (NMA) of FDA-approved JAK inhibitors for alopecia areata (AA) with at least 50% hair loss per SALT score
Some JAK inhibitors are effective for significant hair regrowth in alopecia areata.
research 944 Non-coding double stranded RNA induces retinoic acid synthesis and retinoid signaling to control regeneration
Non-coding RNA boosts retinoic acid production and signaling, aiding regeneration.
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 KRDQN: An Interpretable Prediction Framework for Adverse Drug Reactions via Knowledge–Graph Reinforced Deep Q-Learning
KRDQN effectively predicts adverse drug reactions with high accuracy and clear explanations.
research Explaining and predicting the single channel versus multi-channel consumer: the case of an embarrassing product
The Theory of Planned Behaviour predicts consumer behavior better when emotions, personality, demographics, and marketing are included.
research Association between male pattern baldness and prostate disease: A meta-analysis
Men with male pattern baldness have a higher risk of aggressive prostate cancer and benign prostatic hyperplasia.
research Fronteggiare l’inaffidabilità della letteratura da studi clinici
Public health decisions should rely on independent trials, not biased literature.
research Interventions for central serous chorioretinopathy: a network meta-analysis
The study aims to find the best treatment for central serous chorioretinopathy by comparing various options.
research Alopecia areata and adverse pregnancy outcomes: A systematic review and meta-analysis
research Integrated edge information and pathway topology for drug-disease associations
iEdgePathDDA effectively finds new drug-disease links, outperforming other methods.
research BEYOND HAIR LOSS: EXPLORING THE EVOLUTION OF ANDROGENETIC ALOPECIA RESEARCH BASED ON TEXT MINING AND BIBLIOMETRICS
Data visualization tools are crucial for understanding and advancing androgenetic alopecia research.
research Weakly supervised learning of biomedical information extraction from curated data
The method can effectively extract biomedical information without needing expert annotation, performing better than previous models.
research Artificial neural networks algorithms for prediction of human hair loss related autoimmune disorder problem
Artificial neural networks can accurately diagnose Alopecia Areata.
research Genetically determined metabolites in allergic conjunctivitis: A Mendelian randomization study
Eight blood metabolites are linked to causing allergic conjunctivitis, offering new ways to predict and treat it.
research Faculty Opinions recommendation of There Is a Positive Dose-Dependent Association between Low-Dose Oral Minoxidil and Its Efficacy for Androgenetic Alopecia: Findings from a Systematic Review with Meta-Regression Analyses.
research Conservation of marine habitats under multiple human uses : Methods, objectives and constraints to optimize a Marine Protected Areas network in the Eastern English Channel
Marxan is better for designing Marine Protected Areas in the Eastern English Channel.
research Multiplex matrix network analysis of protein complexes in the human TCR signalosome
Alopecia areata patients show unique protein activity patterns, suggesting imbalanced signaling pathways.
research DNN-DTIs: improved drug-target interactions prediction using XGBoost feature selection and deep neural network
The DNN-DTIs method accurately predicts drug-target interactions and is useful for drug repositioning.
research Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders
A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.
research Trends and techniques: a statistical review of hair care product evaluation research
Better standardization and transparency in statistical reporting are needed to improve hair care research quality.
research Prioritizing Susceptibility Genes for the Prognosis of Male-pattern Baldness with Transcriptome-wide Association Study
The research identified genes linked to male-pattern baldness and potential drug targets for treatment.
research Unraveling the complex role of MAPT-containing H1 and H2 haplotypes in neurodegenerative diseases
H1 increases risk for neurodegenerative diseases, while H2 offers protection but is linked to other disorders.
research JAK-centric explainable few-shot gene-expression diagnosis framework for alopecia via MultiPLIER priors and relation-style set-to-set comparison
A new method helps diagnose alopecia areata using specific gene markers and could guide targeted treatments.
![Benzo[c]quinolizin-3-ones Theoretical Investigation: SAR Analysis and Application to Untested Compounds](/images/research/6712367a-949f-47c7-a756-2bfe6316fc69/small/15331.jpg)
research Benzo[c]quinolizin-3-ones Theoretical Investigation: SAR Analysis and Application to Nontested Compounds
The research found a link between certain molecular features and the biological activity of BC3, which can help identify or create new active compounds.
research Relative efficacy of microneedling in the treatment of pattern hair loss: a protocol for a systematic review with network meta-analysis
Microneedling may be an effective treatment for pattern hair loss.
research Mult-trait analysis of GWAS - Perceived youtfulness - UKBB
The conclusion is that certain traits, including perceived facial aging and BMI, are linked to perceived youthfulness differently in men and women.
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.