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.
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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.
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.
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 Signal Detection for Adverse Events of Finasteride Using Korea Adverse Event Reporting System (KAERS) Database
research DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
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 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 (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 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 Artificial neural networks algorithms for prediction of human hair loss related autoimmune disorder problem
Artificial neural networks can accurately diagnose Alopecia Areata.
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 PEDL-XAI: A Hybrid Probabilistic Ensemble Deep Learning Approach for Hair Disorder Diagnosis
The new AI system accurately diagnoses hair disorders and offers personalized treatment recommendations.
research A Feature-Preserving Hair Removal Algorithm for Dermoscopy Images
The algorithm effectively removes hair from skin images, improving melanoma diagnosis accuracy.
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 Using artificial intelligence to compute Severity of Alopecia Tool scores
AI can accurately measure hair loss severity in alopecia areata.
research Artificial Intelligence in Healthcare – A Review
AI can greatly improve healthcare by enhancing disease prevention, detection, diagnosis, and treatment.
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 Hair & Scalp Disease Detection Using Machine Learning & Image Processing
AI can accurately diagnose hair and scalp conditions and suggest treatments.
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 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 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 Hair and scalp disease detection using deep learning
Deep learning can effectively detect hair and scalp diseases early.
research Multi-Class Support Vector Machine Classification for Detecting Alopecia Areata and Scalp Diseases
The method accurately detects and classifies scalp diseases, including alopecia areata, with 89.3% accuracy.
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 199 Computer vision AI-based androgenetic alopecia analysis using a novel mobile web app
The MDhair app accurately assesses hair loss severity with 94% accuracy.
research Impact of artificial intelligence on healthcare
AI is revolutionizing healthcare by improving diagnosis, treatment, and monitoring, but still needs close supervision.
research BaldPredict: AI-Driven Prediction Model for Alopecia Areata
AI can improve alopecia areata diagnosis with high accuracy.