research Hair Follicle Classification and Hair Loss Severity Estimation Using Mask R-CNN
An intelligent system can classify hair follicles and measure hair loss severity with reasonable accuracy.
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870-900 / 1000+ results research Development and Qualification of a Physiologically Based Pharmacokinetic Model of Finasteride and Minoxidil Following Scalp Application
The model can help predict how finasteride and minoxidil work when applied to the scalp.
research Mapping of cis-acting expression quantitative trait loci in human scalp hair follicles
Researchers identified genes in scalp hair follicles that may affect hair traits and hair loss.
research Identifying effective immune biomarkers in alopecia areata diagnosis based on machine learning methods
Machine learning can help find new ways to treat alopecia areata.
research Phenotypic, transcriptomic, and genomic analyses reveal the spatiotemporal patterns and associated genes of coarse hair density in goats
The gene GJA1 is important for regulating coarse hair density in goats.
research A Study on the Development of a Web Platform for Scalp Diagnosis Using EfficientNet
A web platform was created to help diagnose scalp conditions accurately and easily.
research Detecting shortcut learning for fair medical AI using shortcut testing
The ShorT method can detect and help reduce bias in medical AI by identifying shortcut learning.
research Neurospectrum: A Geometric and Topological Deep Learning Framework for Uncovering Spatiotemporal Signatures in Neural Activity
Neurospectrum effectively analyzes neural signals to predict and identify brain activity patterns better than traditional methods.
research A Potential Predictive Role of the Scalp Microbiome Profiling in Patients with Alopecia Areata: Staphylococcus caprae, Corynebacterium, and Cutibacterium Species
People with severe hair loss (Alopecia Areata) have different scalp bacteria than healthy people, which might help predict the condition's progress.
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 A Combinatorial Tweet Clustering Methodology Utilizing Inter and Intra Cosine Similarity
The method effectively grouped tweets into categories without knowing the number of groups beforehand.
research Data-driven strategies for drug repurposing: insights, recommendations, and case studies
Data-driven methods can effectively identify existing drugs for new uses, especially in cancer, infections, and respiratory diseases.
research Harnessing Microbiome, Bacterial Extracellular Vesicle, and Artificial Intelligence for Polycystic Ovary Syndrome Diagnosis and Management
Microbiome analysis, BEVs, and AI can improve PCOS diagnosis and treatment.
research A Quantitative Measurement Method for Nuclear-Pleomorphism Scoring in Breast Cancer
A new method accurately measures cell changes in breast cancer.
research Protocol for optimized dissociation of human scalp tissue for hair follicle transcriptomics by scRNA-seq
The document provides a method to prepare human scalp tissue for studying hair follicles at the single-cell level.
research A Novel Fusion Technique for Early Detection of Alopecia Areata Using ResNet-50 and CRSHOG
AlopeciaDet accurately detects Alopecia Areata early using advanced image analysis.
research Editorial: Progress and Prospects on Skin Imaging Technology, Teledermatology and Artificial Intelligence in Dermatology
New skin imaging, teledermatology, and AI could become key in future dermatology care.
research TMPRSS2, required for SARS-CoV-2 entry, is downregulated in lung cells by enzalutamide, a prostate cancer therapeutic
A prostate cancer drug can lower the levels of a protein that the coronavirus uses to enter lung cells.
research Harnessing Deep Learning for Scalp and Hair Disease Classification: A Comparative Study of Convolutional Neural Networks Architectures
VGG16 and VGG19 are the most accurate for classifying scalp and hair diseases.
research A pan-European register-based observational study of abrocitinib and conventional systemic therapies in moderate and severe atopic dermatitis: the DREAM TO TREAT AD study protocol
Abrocitinib is being evaluated for safety and effectiveness in treating moderate to severe atopic dermatitis.
research Performance exploration of multi-gene panels of alopecia areata susceptibility and drug-binding targets
Methotrexate, resveratrol, and curcumin may help treat alopecia areata by targeting immune cells.
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 TOWARDS NOVEL DIAGNOSTIC MARKER BASED ON BREAST ARTERIAL CALCIFICATIONS
Detecting early breast arterial calcifications can help assess cardiovascular disease risk.
research An Improved Face Image Restoration Method Based on Denoising Diffusion Probabilistic Models
The new method improves facial image restoration quality and face recognition accuracy.
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 A systems study of nutrient uptake in plants
Improving phosphorus use in crops involves understanding phosphate uptake, with key roles for cellular processes and root structures.
research An Explainable AI-Based Decision Support System for Teaching and Classifying Hair Loss Types
The AI system accurately classifies hair loss types and explains its decisions.
research MSF-VMDNet for multi class segmentation of skin cancer whole slide images using a multi frequency dual encoder network
MSF-VMDNet accurately segments skin cancer images better than existing methods.
research Risk of Safety Events in Vitiligo Patients: A Retrospective Real‐World Data Study in the US
Vitiligo patients have higher risks of autoimmune diseases, infections, and skin cancer.
research Amplitude-guided deep reinforcement learning for semi-supervised layer segmentation
The new method improves accuracy in segmenting scalp tissue layers.