research Machine Learning--Enhanced Pharmacovigilance Assessment of Cardiac Adverse Events Associated With Minoxidil
Minoxidil is strongly linked to heart problems, and machine learning can improve drug safety checks.
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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 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 Objective quantification of chemotherapy-induced madarosis: a pilot study of an automated computer vision pipeline for eyebrow density assessment
The tool accurately tracks eyebrow hair loss in chemotherapy patients.
research How to Assess Dermatology Resident Surgical Training: New Techniques
New evaluation tools are needed for better surgical training in dermatology residency programs.
research Bias Assessment and Data Drift Detection in Medical Image Analysis: A Survey
Reliable machine learning in medical imaging needs bias checks and data drift detection for consistent performance.
research Unraveling the Complex: Changes in Secondary Science Preservice Teachers' Assessment Expertise
Changes in early neurosteroid levels can affect adult learning and anxiety.
research Inferring Spatially Resolved Transcriptomics Data from Whole Slide Images for the Assessment of Colorectal Tumor Metastasis: A Feasibility Study
Using deep learning to predict gene expression from images could help assess colorectal cancer metastasis.
research Analysis of trichoscopic images using deep neural networks for the diagnosis and activity assessment of alopecia areata – a retrospective study
AI can accurately diagnose and assess alopecia areata using scalp images.
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.
research A machine learning approach for non-invasive PCOS diagnosis from ultrasound and clinical features
Machine learning can accurately diagnose PCOS non-invasively using clinical and ultrasound features.
research Machine learning predicts scarring progression in lichen planopilaris: A multidimensional model integrating trichoscopy, vitamin D, and diagnostic timelines
A machine learning model can predict scarring in lichen planopilaris using factors like vitamin D levels and diagnostic delay.
research A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
The system effectively detects scalp diseases and classifies hair fall stages with high precision.
research Genomic and phenotypic characterization of Investigator Global Assessment (IGA) scale-based endotypes in atopic dermatitis
Different types of atopic dermatitis were linked to specific genetic and immune changes, suggesting that severe cases might need stronger immune-targeting treatments.
research Advancing Hair Loss Assessment in Alopecia Areata: The Mathematical Case for Centralised, Standardised Imaging
Centralized imaging provides more accurate and consistent hair loss measurements in alopecia areata.
research Smart Diagnostic System for Health Risk Assessment
WomenCare helps predict PCOD risk in women to encourage early medical consultation.
research ADVANCES IN FUNCTIONAL NEUROSURGERY – MACHINE LEARNING, NEURAL ENGINEERING AND ROBOTICS IN TREATMENT OF NEURODEGENERATIVE DISORDERS
AI and robotics are improving treatment and monitoring of neurodegenerative disorders like Parkinson's.
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 Can online medical education improve management of challenging cases of onychomycosis?
Online medical education helps doctors make better clinical decisions and increases their knowledge in treating fungal nail infections.
research Ensuring safety in cytotoxic drug preparation: A systematic review of guidelines addressing education for pharmacy professionals
Pharmacy professionals need thorough training and guidelines for safely preparing cytotoxic drugs.
research CZY SZTUCZNA INTELIGENCJA MA I BĘDZIE MIAŁA WPŁYW NA EFEKTYWNIEJSZE LECZENIE W CHIRURGII NACZYNIOWEJ?
AI improves vascular surgery by enhancing diagnostics, planning, and monitoring.
research The Transformative Role of Artificial Intelligence in Plastic and Reconstructive Surgery: Challenges and Opportunities
AI can greatly improve plastic surgery, but ethical care and human aspects must remain a priority.
research Demonstrating the potential of untargeted hair proteomics for personalized biomarkers in stress-associated disorders
Hair proteomics could be a useful, non-invasive tool for identifying stress-related disorders.
research Non-invasive skin measurement methods and diagnostics for vitiligo: a systematic review
Reliable, non-invasive tools are needed for better vitiligo diagnosis.
research Innovative Teaching Strategies for Medical Students: Encouraging Reflection on Patient Experiences Through Creative Methods and Meaningful Connections
Medical education should use creative and reflective methods to enhance empathy and critical thinking.
research The Assessment and Management of Tinea Capitis in Children
Oral medication is necessary to treat scalp fungus in children, with griseofulvin being the usual choice.
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 Hair and scalp disease detection using deep learning
Deep learning can effectively detect hair and scalp diseases early.
research Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study
Machine learning can predict symptoms and quality of life in chronic skin disease patients using smartphone app data, and shows that app use varies with patient characteristics.
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.