research Hair cluster detection model based on dermoscopic images
The new model detects hair clusters more accurately and efficiently, helping with early hair loss treatment and diagnosis.
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research Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets
The new method improves skin cancer detection in imbalanced datasets.
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 Quantitative analysis and development of alopecia areata classification frameworks
A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.
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 Artificial neural networks algorithms for prediction of human hair loss related autoimmune disorder problem
Artificial neural networks can accurately diagnose Alopecia Areata.
research Trichoscopy of Alopecia Areata: Hair Loss Feature Extraction and Computation Using Grid Line Selection and Eigenvalue
Researchers developed an algorithm for self-diagnosing scalp conditions with high accuracy using smart device-attached microscopes.
research γδ17 T cell-stromal networks modulate matrix composition and vascularity in foreign body response
γδ T cells help control tissue scarring and blood vessel growth in response to foreign objects.
research 1040 Photographing alopecia - How many pixels are needed for clinical evaluation?
Higher resolution images are needed to identify scarring and fine hair in alopecia.
research Hair Disease Classification Using Convolutional Neural Network (CNN) Algorithm with VGG-16 Architecture
The system can accurately classify hair diseases with 94.5% accuracy using a CNN.
research An Integrated Approach for Diabetes Detection Using Fisher Score Feature Selection and Capsule Network
The method accurately detects diabetes with 94% effectiveness, reducing misdiagnosis risk.
research Generative adversarial networks for anonymous acneic face dataset generation
The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.
research AB-MTEDeep Classifier Trained with AAGAN for the Identification and Classification of Alopecia Areata
The AI model accurately classifies Alopecia Areata with 96.94% accuracy.
research Diagnosis of Scalp Disorders using Machine Learning and Deep Learning Approach -- A Review
Deep learning effectively diagnoses scalp disorders, but improvements are needed.
research Evaluation of Automated Measurement of Hair Density Using Deep Neural Networks
Deep learning can accurately automate hair density measurement, with YOLOv4 performing best.
research NLKFill: high-resolution image inpainting with a novel large kernel attention
NLKFill improves high-resolution image inpainting by effectively capturing image details and enhancing speed.
research Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions
Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
research Neural Mechanisms of Hair Growth Control
Nerves and chemicals in the body can affect hair growth and loss.
research Motoneuron-Specific PTEN Deletion in Mice Induces Neuronal Hypertrophy and Also Regeneration after Facial Nerve Injury
Deleting the PTEN gene in mice causes nerve cells to grow larger and heal better after injury, but may cause overgrowth and hair loss in older mice.
research Do Alpha-Blockers and 5-Alpha Reductase Inhibitors Increase Dementia Risk? A Network Meta-analysis
Alpha-blockers and 5-alpha reductase inhibitors don't significantly increase dementia risk.
research Scalp Disorder Imaging: How Deep Learning and Explainable Artificial Intelligence are Revolutionizing Diagnosis and Treatment
Deep learning and explainable AI are improving scalp disorder diagnosis, but challenges in transparency and data quality remain.
research Enhancing Hairfall Prediction: A Comparative Analysis of Individual Algorithms and An Ensemble Method
Combining multiple algorithms predicts hair fall more accurately than using single algorithms.
research A human prenatal skin cell atlas reveals immune cell regulation of skin morphogenesis
Immune cells are essential for early hair and skin development and healing.
research Three-dimensional ultrastructural analysis of human skin with the arrector pili muscle interacting with the hair follicle epithelium
The method effectively analyzes skin tissue changes, especially in the arrector pili muscle and nerve fibers with hair follicles.
research Ca 2+ -mediated protein citrullination regulates proliferation in the regenerating and malignant CNS
Ca²⁺-mediated protein citrullination controls cell growth in the CNS and may help treat brain tumors.
research Cryogelation of human hair keratins
Human hair keratins can be turned into useful 3D biomedical scaffolds through a freeze-thaw process.
research Artificial Intelligence in Healthcare – A Review
AI can greatly improve healthcare by enhancing disease prevention, detection, diagnosis, and treatment.
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 Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review
Computer vision techniques can help detect and assess skin conditions like vitiligo, alopecia areata, and dermatitis.
research The Microanatomy of Human Skin in Aging
Aging skin shows thinner layers, fewer hair follicles, and new biomarkers like increased space between cells and smaller sebaceous glands.