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 Machine Learning Approach for Predicting Systemic Lupus Erythematosus in Oman-based Cohort
The machine learning model accurately predicts Systemic Lupus Erythematosus in Omani patients.
research Re-identification of anonymised MRI head images with publicly available software: investigation of the current risk to patient privacy
research AutoMIR: Effective Zero-Shot Medical Information Retrieval without Relevance Labels
SL-HyDE improves medical information retrieval accuracy without needing labeled data.
research Multiscale Morphological Reconstruction for Hair Removal in Dermoscopy Images
The method accurately detects and removes hair from skin images to improve melanoma diagnosis.
research Balancing Benefits and Limitations of Artificial Intelligence in Cosmetic Surgery
AI improves cosmetic surgery but requires ethical and legal oversight to ensure safe use.
research Robotic Hair Harvesting System: A New Proposal
A proposed robotic system could make hair harvesting for baldness treatment faster and more precise.
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.
research Improved forensic hair evidence for drugs of abuse by mass spectrometry
Forensic hair analysis for drugs is now more reliable and accurate.
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 Development and Assessment of an Artificial Intelligence–Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners in Teledermatology Practices
The AI tool helped primary care doctors and nurse practitioners diagnose skin conditions more accurately.
research Rethinking pattern hair loss classification in the era of trichoscopy and artificial intelligence
A hybrid model using traditional methods, trichoscopy, and AI improves hair loss assessment.
research Boundary-aware Multi-stage with Mobile U-Net for Hair Segmentation in Dermoscopic Images
The new method improves hair segmentation in skin images, helping detect skin cancer more accurately.
research Hair analysis for monitoring drug use
Hair analysis can effectively monitor long-term drug use.
research Heed Early Signs
Pay attention to early warnings.
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 The Price Waterhouse Guide to Financial Management: Tools for Improving Performance
A new method can quickly detect alcohol abuse by analyzing hair in under an hour.
research Testing for GHB in Hair by GC/MS/MS after a Single Exposure. Application to Document Sexual Assault
Hair testing can detect a single GHB exposure, useful for documenting sexual assault.
research Effective holistic characterization of small molecule effects using heterogeneous biological networks
Integrating biological networks improves drug repurposing and ADR prediction.
research Use of the TrichoScan to Assess Female Pattern Hair Loss
TrichoScan helps identify subtle hair thinning in women with androgenetic alopecia.
research Hair analysis based on medical history and spatial-temporal data
Machine learning can predict hair health accurately using personal data.
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 Case report - hair tourniquet syndrome
Hair tourniquet syndrome can cause serious harm and may indicate child abuse.
research Early prediction of alopecia areata using machine learning modeling of neuro stress immune signatures from multi datasets
A machine learning model can predict alopecia areata early using specific gene markers.
research Comprehensive HPLC and UPLC-MS/MS Analysis for the Multi-component Detection of Hair Growth Compounds in Consumer Health Products
A reliable method was developed to detect hair growth compounds in products, ensuring safety and compliance.
research A Machine Learning Algorithm Applied to Trichoscopy for Androgenic Alopecia Staging and Severity Assessment
The machine learning model effectively assesses the severity of hair loss and could help dermatologists with treatment decisions.
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 Development and application of emotion recognition technology — a systematic literature review
Emotion recognition tech helps devices understand emotions, but more research is needed for complex situations.
research Amplitude-guided deep reinforcement learning for semi-supervised layer segmentation
The new method improves accuracy in segmenting scalp tissue layers.
research Emergency Wound Infection Monitoring and Treatment Based on Wearable Electrochemical Detection and Drug Release with Conductive Hydrogel
A new wearable system improves wound healing by monitoring infections and delivering precise treatment.