research Attention Balanced Multi-Dimension Multi-Task Deep Learning for Alopecia Recognition
The new deep learning system can accurately recognize hair loss conditions with a 95.11% success rate.
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480-510 / 1000+ results research NEUROSENSORY ECOLOGY IN THE JEB
Different species have unique sensory adaptations to perceive their environments.
research Computational derivation of a molecular framework for hair follicle biology from disease genes
The research provides a gene-based framework for hair biology, highlighting the Hippo pathway's importance and suggesting links between hair disorders, cancer pathways, and the immune system.
research Predictive Metagenomic Profiling, Urine Metabolomics, and Human Marker Gene Expression as an Integrated Approach to Study Alopecia Areata
Alopecia areata may be linked to scalp microbiome differences, suggesting potential treatments with prebiotics, probiotics, and postbiotics.
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 scMC learns biological variation through the alignment of multiple single-cell genomics datasets
scMC effectively separates biological signals from technical noise in single-cell genomics data.
research Rule-out test for autism using machine-learning analysis of molecular temporal dynamics in hair - a multicenter study
A machine-learning test using hair can help detect autism early in infants.
research National, Regional, and Global Epidemiology of Alopecia Areata: A Systematic Analysis Based on Modeling Study
Alopecia areata affects about 1.93% of people worldwide, with more women affected than men.
research Therapeutic Burden as Predictor of Response to Baricitinib for Alopecia Areata in Real Life: Prospective Study
Patients with fewer past treatments for alopecia areata respond better to baricitinib.
research This Month in the Journal
The AR gene is linked to male-pattern baldness, TNFSF4 to heart disease, SLC19A3 to BBGD, MCT8 to a syndrome, and segmental duplications to genetic variation.
research Causal Link of Distinct Mental Disorders with Androgenetic Alopecia and Alopecia Areata: A Bidirectional Two-Sample Mendelian Randomization Study
Major depression disorder increases the risk of alopecia areata, and vice versa.
research Efficacy of modern methods for assessing the severity of alopecia areata
The SBN system effectively assesses alopecia areata severity and predicts its course.
research Association Between Male Androgenetic Alopecia and Metabolic Syndrome: Systematic Review and Meta-analysis
Balding men are more likely to have metabolic syndrome.
research Advancing Hair Loss Assessment in Alopecia Areata: The Mathematical Case for Centralised, Standardised Imaging
Centralized imaging provides more accurate and consistent hair loss measurements in alopecia areata.
research Bibliometric and visualized analysis of nonpharmaceutical TCM therapies for rheumatoid arthritis over the last 20 years using VOSviewer and CiteSpace software
research Multivariate analysis of clinical characteristics and prognostic factors in early-onset alopecia areata: a retrospective study with 82 Brazilian patients
research Author response for "Repeated finasteride administration promotes synaptic plasticity and produces antidepressant‐ and anxiolytic‐like effects in female rats"
research Identification of Key Genes and Signaling Pathways in Male Androgenetic Alopecia by Bioinformatics Analysis
Found key genes affecting hair loss, immune response, and skin development; more research needed for better treatments.
research A Hybrid Transfer Learning Approach Using Obesity Data for Predicting Cardiovascular Diseases Incorporating Lifestyle Factors
Adding obesity data to machine learning models improves heart disease prediction accuracy.
research A Comprehensive Review of Alopecia Areata Detection Using Self-Supervised Auto ML Models: Systematic Insights and Emerging Challenges
AI models are effective for detecting alopecia areata but face challenges like explaining results and data bias.
research A Critical Evaluation of Evaluations for Long-form Question Answering
Current methods can't accurately predict which long-form answers people prefer; evaluations should consider different answer qualities separately.
research Faculty Opinions recommendation of Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria.
PCOS shares similar genetic traits across different diagnosis criteria and is linked to other health conditions.
research KEBOT: An Artificial Intelligence Based Comprehensive Analysis System for FUE Based Hair Transplantation
The KEBOT system is a highly accurate AI tool for analyzing hair transplants.
research AnnoPharma: Detection of substances responsible of ADR by annotating and extracting information from MEDLINE abstracts
AnnoPharma effectively identifies substances causing adverse drug reactions in medical abstracts.
research The Cochrane Database of Systematic Reviews - Issue 8 2012
The issue included new and updated reviews on various health interventions, with significant findings on weight loss, psychological therapies, cancer treatment, and more.
research Prediction of gain-of-function and loss-of-function mutations using Combined Annotation Dependent Depletion (CADD)
C-scores can help predict gain-of-function and loss-of-function mutations.
research Causal effects of genetically determined metabolites on androgenetic alopecia: A two‐sample Mendelian randomization analysis
Certain metabolites can either protect against or increase the risk of hair loss.
research 397 Predictive modeling of drug response and mechanism of action in alopecia areata clinical trials
Researchers found three different ways drugs work to treat hair loss from alopecia areata and identified key factors for personalized treatment.
research RETRACTED: Causal role of immune cells in alopecia areata: A two‐sample Mendelian randomization study
The study suggested certain immune cells might cause alopecia areata, but it was retracted.
research Cost-effectively dissecting the genetic architecture of complex wool traits in rabbits by low-coverage sequencing
Low-coverage sequencing is a cost-effective way to identify genes related to wool traits in rabbits.