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.
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60-90 / 1000+ resultsresearch Circulating MicroRNA Signatures in Severe Alopecia Areata: Diagnostic Discrimination, Pathway Analysis, and Therapeutic Implications
Specific miRNA profiles can help diagnose and treat alopecia areata.
research Unique Circulating MicroRNA Signatures Distinguish Severe Alopecia Areata from Other Inflammatory Skin Diseases
Unique microRNA patterns can help diagnose and treat severe alopecia areata.
research Integrated single-cell chromatin and transcriptomic analyses of human scalp reveal etiological insights into genetic risk for hair and skin disease
The research provided new insights into the genetic factors contributing to hair loss and skin conditions by analyzing individual cells from the human scalp.
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 Nanotechnology-Based Strategies for Hair Regeneration: Mechanistic Insights and Translational Perspectives for Androgenetic Alopecia
Nanotechnology offers promising new treatments for hair loss by improving targeted delivery and addressing key causes.
research Identification and single-cell analysis of prognostic genes related to mitochondrial and neutrophil extracellular traps in bladder cancer
Six key genes can predict bladder cancer outcomes and may serve as prognostic biomarkers.
research Abstracts from the 55th European Society of Human Genetics (ESHG) Conference: Oral Presentations
NIPT can help detect potential maternal cancer, and GIPXplore can identify immune diseases in pregnancies.
research 8280186 Biomarkers for Occupational Hand Eczema: Improving Diagnostic Differentiation
Certain biomarkers can help distinguish between irritant and allergic contact dermatitis.
research The 3D Bioprinted Scaffolds for Wound Healing
3D bioprinting improves wound healing by precisely creating scaffolds with living cells and biomaterials, but faces challenges like resolution and speed.
research Emerging smart microneedle technologies in psoriasis: convergence of nanocarriers, machine learning, and personalized delivery
Smart microneedles using advanced tech could improve psoriasis treatment.
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 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.
research Global Research Trends for Platelet-Rich Plasma: A Science Mapping with Machine Learning Techniques
The USA, China, Italy, and Türkiye lead in diverse PRP research, focusing on healing and pain management.
research Identification of SLC40A1, LCN2, CREB5, and SLC7A11 as ferroptosis-related biomarkers in alopecia areata through machine learning
Four genes are potential markers for hair loss condition alopecia areata, linked to a specific type of cell death.
research Construction of regulatory network for alopecia areata progression and identification of immune monitoring genes based on multiple machine-learning algorithms
Researchers found four genes that could help diagnose severe alopecia areata early.
research Machine Learning Guided Discovery of Superoxide Dismutase Nanozymes for Androgenetic Alopecia
Machine learning identified promising nanozymes for treating hair loss.
research Machine learning driven multi-omics analysis of the genetic mechanisms behind the double-coat fleece formation in Hetian sheep
Key genes IRF2BP2 and EGFR are linked to Hetian sheep's double-coat fleece.
research Optimizing skin disease diagnosis: harnessing online community data with contrastive learning and clustering techniques
Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
research An Early Hair Loss Detection and Prediction Method Based on Machine Learning
Machine learning can accurately predict hair loss early, improving treatment options.
research Machine Learning Applications for Drug Repurposing
Machine learning helps find new uses for existing drugs, improving healthcare.
research Research on Mental Stress Recognition of Depressive Disorders in Patients With Androgenic Alopecia Based on Machine Learning and Fuzzy K-Means Clustering
The FAW-FS algorithm improves depression recognition, and psychological interventions help AGA patients' mental health.
research Ensemble of pre-learned deep learning model and an optimized LSTM for Alopecia Areata classification
The new model improves Alopecia Areata classification accuracy to 93.1%.
research Scalp disease analysis using deep learning models
Deep learning models can analyze scalp diseases effectively.
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.
research GBP1 as a machine learning-prioritized biomarker and therapeutic target for epstein-barr virus-induced clear cell renal cell carcinoma: multi-omics causal validation
GBP1 is a key target for treating Epstein-Barr virus-related kidney cancer, and finasteride may help.
research Integrated multiple machine learning and Mendelian randomization reveal LTF gene as a prognostic biomarker for nonspecific orbital inflammation
The LTF gene may help predict and manage nonspecific orbital inflammation.
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.
research Treatment options and emotional well-being in patients with rosacea: An unsupervised machine learning analysis of over 200,000 posts
Rosacea patients often discuss treatments and emotional struggles online, highlighting the need for professional support.