research Serum-Based Assessment of Alopecia Areata Response to Treatment Using ATR-FTIR Spectroscopy
ATR-FTIR spectroscopy could help monitor alopecia areata treatment response non-invasively.
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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.
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 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.
research Non-invasive skin measurement methods and diagnostics for vitiligo: a systematic review
Reliable, non-invasive tools are needed for better vitiligo diagnosis.
research Raman investigation of in vivo radiation exposure on melanin in murine hair
Raman spectroscopy can detect radiation exposure in mouse hair with high accuracy for up to 7 days.
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 Drug repurposing: Clinical practices and regulatory pathways
Drug repurposing offers faster, cheaper drug development but faces challenges like safety, ethics, and funding.
research Past, Present and Future Perspectives of Forensic Genetics
Forensic genetics can now predict physical traits and lifestyle habits, with future advancements expected from new technologies.
research Integration of Colorimetric Sensing Dyes and Multi‐Substrate Arrays for Food Quality and Safety Monitoring: Design, Optimization, and Analysis
Combining advanced sensors with portable devices could enhance on-site food safety monitoring.
research 3D organotypic skin models recapitulate autoantibody-driven pemphigus pathomechanisms and targeted therapeutic response
The 3D skin model mimics pemphigus vulgaris and helps test treatments.
research Repurposing With Purpose: Treatment of Bachmann–Bupp Syndrome With Eflornithine and Implications for Other Polyaminopathies
Eflornithine improved symptoms in Bachmann–Bupp Syndrome patients.
research Decoding Gut Microbiome Dysbiosis as a Non-Invasive Diagnostic Biomarker for Alopecia Areata
Gut bacteria differences could help diagnose and treat alopecia areata.
research Cell cycle controls long-range calcium signaling in the regenerating epidermis
Calcium signaling in skin cells is crucial for communication and regeneration.
research MultiKano: an automatic cell type annotation tool for single-cell multi-omics data based on Kolmogorov–Arnold network and data augmentation
MultiKano accurately identifies cell types in complex data better than existing methods.
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 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 Hair and scalp disease detection using deep learning
Deep learning can effectively detect hair and scalp diseases early.
research Penerapan Algoritma Naive Bayes untuk Prediksi Kerontokan Rambut
Naive Bayes algorithm can help predict hair loss risk early.
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 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 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 Artificial Intelligence Deep Learning Ultrasound Discrimination of Cosmetic Fillers
AI can accurately identify some cosmetic fillers in ultrasound images but needs improvement for others.
research ScalpEye: A Deep Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health
ScalpEye accurately diagnoses scalp issues like dandruff and hair loss.
research BaldGraphFormer: An Explainable Deep Learning Framework for Early Baldness Prediction by Integrating Swin Transformer, Graph Attention Networks and Clinical Features
BaldGraphFormer accurately predicts early baldness, aiding better hair loss treatment.
research Repurposing FDA approved drugs for psoriasis indications through integrated molecular docking, one-SVM algorithm, and molecular dynamics simulation approaches
Pioglitazone, Trimipramine, and Dimetindene may be repurposed to treat psoriasis.
research DEEP REINFORCEMENT LEARNING FOR SCALABLE CONTROL OF BOOLEAN MODELS IN THE CONTEXT OF CELLULAR REPROGRAMMING
pbn-STAC effectively finds strategies for cellular reprogramming using deep reinforcement learning.
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 Comparison of Linear Regression, Decision Tree Regression, and Random Forest Regression Algorithms in Predicting Baldness Risk
Random Forest Regression is best for predicting baldness risk.
research How good is artificial intelligence (AI) at solving hairy problems? A review of AI applications in hair restoration and hair disorders
AI is effective in diagnosing and treating hair disorders, including detecting hair loss and scalp conditions with high accuracy, but it should supplement, not replace, doctor-patient interactions.