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.
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360-390 / 1000+ results 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.
research Assessment of college students’ mental health status based on temporal perception and hybrid clustering algorithm under the impact of public health events
A new method accurately measures college students' mental health by considering time perception and clustering techniques.
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 ARTIFICIAL INTELLIGENCE TECHNIQUES IN PREDICTION OF COVID-19 MORTALITY AND ITS RELATED FACTORS: A MULTI-CENTER STUDY
AI can effectively predict COVID-19 mortality risk using patient data.
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.
research A Review on the Form and Complexity of Human–Robot Interaction in the Evolution of Autonomous Surgery
Human-robot interaction becomes simpler as robots achieve full autonomy in surgery.
research Enhancing Low-Light Sports Motion Images with Improved Bilateral Filtering and Auto MSRCR
The method greatly improves low-light sports images' quality and reduces artifacts.
research 48853 The AI Doctor will see you now: Can ChatGPT-4 be used to safely counsel patients with allergic contact dermatitis?
ChatGPT-4 can help with allergic contact dermatitis but shouldn't replace expert doctors.
research Hair and Scalp Disease Detection using Machine Learning and Image Processing
The machine learning model accurately detected hair loss and scalp diseases using processed images.
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 An Approach to Detect Alopecia Areata Hair Disease Using Deep Learning
Deep learning can accurately detect Alopecia Areata with up to 98.3% accuracy.
research A Comparative Study of Machine Learning Algorithms in Predicting Mental Disorders
Machine learning can accurately predict mental disorders.
research 0040 Machine learning algorithms as tools for identifying predictive autoantibody biomarkers in pemphigus vulgaris
Machine learning can help identify biomarkers for personalized Pemphigus vulgaris treatment.
research Trichoscopy of Alopecia Areata: Hair Loss Feature Extraction and Computation Using Grid Line Selection and Eigenvalue
Researchers developed an algorithm for self-diagnosing scalp conditions with high accuracy using smart device-attached microscopes.
research Robotic Hair Harvesting System: A New Proposal
A proposed robotic system could make hair harvesting for baldness treatment faster and more precise.
research HERBSNAP: Advanced Classification of Bhringaraja and Honegone Herbal Species
Machine learning can accurately tell apart False Daisy and Smooth Joy Weed.
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 AutoMIR: Effective Zero-Shot Medical Information Retrieval without Relevance Labels
SL-HyDE improves medical information retrieval accuracy without needing labeled data.
research Case report - hair tourniquet syndrome
Hair tourniquet syndrome can cause serious harm and may indicate child abuse.
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 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.