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.
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research Automating Hair Loss Labels for Universally Scoring Alopecia From Images
The AI system HairComb accurately scores hair loss severity, matching dermatologist assessments.
research RESEARCHComparing Strategies for Identifying Falls in Older Adult Emergency Department Visits Using EHR Data
Natural language processing is the most accurate method for identifying falls in older adults in emergency departments.
research 201 Pain digital biomarker detecting by epidermal biopotential flexible sensor and AI-based system
A new pain-measuring system using sensors and AI can effectively detect pain in mice, which may help assess pain in humans and develop treatments.
research DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
research AI03 Steps towards safely deploying the world’s first autonomous artificial intelligence as a medical device for skin cancer into a National Health Service teledermatology pathway
An AI device for skin cancer was successfully integrated into the NHS, improving diagnosis accuracy and service capacity.
research Rapid Screening of Anticoagulation Compounds for Biological Target-Associated Adverse Effects Using a Deep-Learning Framework in the Management of Atrial Fibrillation
The framework helps predict adverse effects of blood thinners, improving drug selection for atrial fibrillation.
research Using morphological operators and inpainting for hair removal in dermoscopic images
The new algorithm removes hair from skin images better than previous methods, helping diagnose melanoma.
research Artificial neural networks algorithms for prediction of human hair loss related autoimmune disorder problem
Artificial neural networks can accurately diagnose Alopecia Areata.
research (Un)targeted Scanning of Locks of Hair for Drugs of Abuse by Direct Analysis in Real Time–High-Resolution Mass Spectrometry
A new method can quickly and accurately detect drugs in hair.
research Hair & Scalp Disease Detection Using Machine Learning & Image Processing
AI can accurately diagnose hair and scalp conditions and suggest treatments.
research Artificial Intelligence in Healthcare – A Review
AI can greatly improve healthcare by enhancing disease prevention, detection, diagnosis, and treatment.
research Progress in computer-assisted function analysis
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 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 Using artificial intelligence to compute Severity of Alopecia Tool scores
AI can accurately measure hair loss severity in alopecia areata.
research Exploring the Potential Routine Use of Electronic Healthcare Record Data to Strengthen Early Signal Assessment in UK Medicines Regulation: Proof-of-Concept Study
Using electronic health records can help identify drug side effects but has some limitations.
research Impact of Reporter Type on Signal Detection of Cancer Therapy-Induced Alopecia: A Hypothesis-Generating Study Using the FDA Adverse Event Reporting System
Reporter characteristics affect detection of hair loss from cancer therapy.
research Dermacen Analytica: A Novel Methodology Integrating Multi-Modal Large Language Models with Machine Learning in tele-dermatology
The new AI system improves remote skin condition diagnosis and access to care.
research HAIR ANALYSIS FOR DRUGS OF ABUSE. PLAUSIBILITY OF INTERPRETATION
Hair analysis can detect drug use but requires careful interpretation due to its complexity.
research HairLossMultinet: A Multi Scale Feature Fusion Method Using Deep Learning Approach
HairLossMultinet accurately classifies hair damage with 98% accuracy but needs a more diverse dataset for broader use.
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 ANÁLISES COMPUTACIONAIS PREDITIVAS COMO UM NOVO BIOPODER: MODIFICAÇÕES DO TEMPO NA SOCIEDADE DOS SENSORES
Predictive computational analyses have evolved biopower by using technology to track and predict individual and group behaviors.
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 Hair and scalp disease detection using deep learning
Deep learning can effectively detect hair and scalp diseases early.
research DEEP REVIEW ON ALOPECIA AREATA DIAGNOSIS FOR HAIR LOSS-RELATED AUTOIMMUNE DISORDER PROBLEM
Machine learning and deep learning can effectively diagnose alopecia areata.
research 115 AE法による実機水車発電機軸受の診断(セッション4 評価・診断II)
KSR1 is crucial for certain skin tumor formation and could be a cancer therapy target.
research A Feature-Preserving Hair Removal Algorithm for Dermoscopy Images
The algorithm effectively removes hair from skin images, improving melanoma diagnosis accuracy.
research Applying Machine Learning Technique on Registry Data to Assess Factors Associated With In-Hospital Mortality Among STEMI Patients With Hypertension
research Classification Framework for Healthy Hairs and Alopecia Areata: A Machine Learning (ML) Approach
Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.