research Optimizing skin disease diagnosis: harnessing online community data with contrastive learning and clustering techniques
Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
Search
for
Sort by
Research
30-60 / 1000+ results 
research Emerging smart microneedle technologies in psoriasis: convergence of nanocarriers, machine learning, and personalized delivery
Smart microneedles using advanced tech could improve psoriasis treatment.
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 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 Hair & Scalp Disease Detection Using Machine Learning & Image Processing
AI can accurately diagnose hair and scalp conditions and suggest treatments.
research A machine learning and network framework to discover new indications for small molecules
A machine learning model called CATNIP can predict new uses for existing drugs, like using antidepressants for Parkinson's disease and a thyroid cancer drug for diabetes.
research Sex-Specific Basal Metabolic Rate and NAFLD Risk: The Multi-Population Observational and Mendelian Randomization Study
Higher basal metabolic rate increases the risk of non-alcoholic fatty liver disease, especially in Chinese people, and may require tailored management.
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 A Hybrid Transfer Learning Approach Using Obesity Data for Predicting Cardiovascular Diseases Incorporating Lifestyle Factors
Adding obesity data to machine learning models improves heart disease prediction accuracy.
research DEEP REINFORCEMENT LEARNING FOR SCALABLE CONTROL OF BOOLEAN MODELS IN THE CONTEXT OF CELLULAR REPROGRAMMING
pbn-STAC effectively finds strategies for cellular reprogramming using deep reinforcement learning.
research Harnessing Deep Learning for Scalp and Hair Disease Classification: A Comparative Study of Convolutional Neural Networks Architectures
VGG16 and VGG19 are the most accurate for classifying scalp and hair diseases.
research Weakly supervised learning of biomedical information extraction from curated data
The method can effectively extract biomedical information without needing expert annotation, performing better than previous models.
research Midazolam Inhibits Hippocampal Long-Term Potentiation and Learning through Dual Central and Peripheral Benzodiazepine Receptor Activation and Neurosteroidogenesis
Midazolam impairs learning and memory by increasing neurosteroids through specific receptor activation.
research Comparative Analysis of Machine Learning Algorithms in Diagnosis of Polycystic Ovarian Syndrome
The Random Forest algorithm was the most accurate at diagnosing Polycystic Ovarian Syndrome.
research A DEEP LEARNING APPROACH FOR DIAGNOSIS OF COVID-19 INFECTION AND ITS RELATED FACTORS: A POPULATION-BASED STUDY
The random forest model effectively helps diagnose COVID-19 using key factors like age and symptoms.
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 Avaliação de respostas defensivas associadas ao pânico em ratas: perfil da ativação serotonérgica no núcleo dorsal da rafe e substância cinzenta periaquedutal
Female rats showed more panic-related behavior than males, influenced by hormonal cycles and certain drugs.
research Comprehensive Program Planning for the Integration of 21st Century Learning Center After-School Programs with Regular Day Programs and Community Partners.
The report expanded knowledge of MBTPS1-related disorders by identifying new symptoms.
research A Comprehensive Survey on Vitiligo Detection Using Deep Learning
Better datasets and methods are needed for reliable vitiligo detection using deep learning.
research Construction of regulatory network for alopecia areata progression and identification of immune monitoring genes based on multiple machine-learning algorithms
Researchers found four genes that could help diagnose severe alopecia areata early.
research Global Research Trends for Platelet-Rich Plasma: A Science Mapping with Machine Learning Techniques
The USA, China, Italy, and Türkiye lead in diverse PRP research, focusing on healing and pain management.
research What do users in a polycystic ovary syndrome (PCOS) forum think about the treatments they tried: Analysing treatment sentiment using machine learning
PCOS forum users view lifestyle changes and supplements positively, but have mixed feelings about contraceptive pills.
research Identification of SLC40A1, LCN2, CREB5, and SLC7A11 as ferroptosis-related biomarkers in alopecia areata through machine learning
Four genes are potential markers for hair loss condition alopecia areata, linked to a specific type of cell death.
research Generating detailed intercellular communication patterns in psoriasis at the single-cell level using social networking, pattern recognition, and manifold learning methods to optimize treatment strategies
New insights into cell communication in psoriasis suggest innovative drug treatments.
research Animals in Dermatology
Using animal names for skin conditions helps with learning and memory.
research Editorial: Machine Learning Techniques on Gene Function Prediction Volume II
Machine learning is effective in predicting gene functions and their relationships with diseases.
research Alopecia Areata: The Clinician and Patient Voice
Alopecia areata causes unpredictable hair loss and emotional distress, with no cure and limited treatment options.
research Robotic Hair Restoration
The ARTAS robotic system for hair restoration is efficient with fewer cuts than manual methods, but it's limited to certain hair types and can still leave scars.
research Current Practices and Controversies in Cosmetic Hair Restoration
The document concludes that hair restoration has advanced significantly, with FUE becoming more popular, and stresses the importance of physician training and ethical practices in the field.
research Deep Learning Approaches for Hair Disease Classification: A Comparative Analysis of MobileNetV2 and VGG19 Architectures
VGG19 is more accurate, but MobileNetV2 is faster and uses fewer resources.